Methods of Novel Therapeutic Candidate Identification Through Gene Expression Analysis in Vascular-Related Diseases

ABSTRACT

Multiple treatment regimens for vascular-related diseases and disorders. Methods of treating vascular-related disorders based on gene expression studies from samples collected from individuals having symptoms of vascular-related disorders. Additionally, methods for diagnostic techniques to focus treatment regimens. Finally, methods of treating vascular-related disorders involving targeting microRNAs.

CROSS-REFERENCES

This application claims the benefit of priority of U.S. Provisional Application Ser. No. 61/040,065, filed on Mar. 27, 2008, the disclosure of which is hereby incorporated by referenced in its entirety.

FIELD OF THE INVENTION

The present invention relates to assessment and identification of expression of genes related to vascular-related diseases. The present invention also includes methods of comparing gene expression patterns with respect to various disease states.

BACKGROUND OF THE INVENTION

Pulmonary arterial hypertension (PAH) is an occlusive disease of the pulmonary arteries leading to serious hemodynamic abnormality, right heart failure, and premature death. The molecular mechanisms behind PAH are still unclear. Without a more complete understanding of PAH and how its complex vascular dysfunctions relate to one another, patients will suffer from imprecise diagnosis and drug therapy that may be less than optimal. Despite recent advances and introduction of new clinically approved drugs, the 5-year survival from pulmonary hypertension remains an estimated 50% (Archer and Rich, 2000). Consequently, treatment for PAH, while recently improved, still offers significant and long-lasting improvement in only a minority of patients. A methodology to elucidate the molecular pathways associated with PAH could guide the development of new therapies for this disease.

Though platelets and other cells may have a role in PAH, pulmonary endothelial cells and pulmonary smooth muscle cells appear to be the primary sites of disease progression (Humbert et al 2004). Molecular pathways that show abnormality in pulmonary endothelial cells and pulmonary smooth muscle cells during PAH include endothelin-1 (Giaid et al 1993), serotonin & serotonin transporter (Marcos et al 2003), thromboxane (Walmrath et al 1997), nitric oxide synthase (Kobs and Chesler 2006), prostacyclins (Gailes, et al 2001), potassium channels (Mandegar et al 2002), BMP signaling (Eddahibi et al 2002), and survivin (McMurtry et al 2005). PAH impairs normal signaling and growth in both pulmonary endothelial and pulmonary smooth muscle cells, yet the cellular abnormalities seem to shift over time in unpredictable patterns that has thus far escaped concise definition (Michelakis, 2006).

PAH may be understood as proceeding in phases. In early PAH, endothelial apoptosis occurs, probably resulting in pulmonary arteriole plugging and an increase in pulmonary vascular pressure (Michelakis, 2006). In late PAH, chronic exposure to elevated pulmonary artery pressure together with dysfunctional endothelial signaling initiates hyperproliferation of smooth muscle cells (McMurtry et al 2005). Increased concentric pulmonary smooth muscle cell proliferation leads to ever increasing pulmonary artery pressure, right ventricular failure, and death.

Lung pathology in all PAH patients show thickening throughout the arterial wall of the pulmonary vascular bed. In some forms of the disease, the pulmonary vascular lesions are reversible (e.g. in newborns with congenital heart defects). In other patients, such as those with the idiopathic form, the lesions are irreversible. It is unknown how these variations in PAH relate to one another on a molecular basis (Pearl et al 2002).

Current therapies for PAH patients primarily target vascular tone. Treatments that aim at correcting potassium channel dysfunction (Machado et al 2001), nitric oxide impairment (Humbert et al 2004), prostacyclin impairment (Tuder et al 1999, Christman et al 1992), and endothelin-1 expression (Giaid et al 1993) have all been clinically available for several years. These therapies offer some relief from hemodynamic symptoms, but most patients show only a transient response. The proliferative disease continues to progress in most PAH patients, resulting in a five year mortality rate that remains at around 50% (Newman et al 2004).

Currently, there are no clinically available routine means to obtain endothelial and smooth muscle samples from the pulmonary arteries of pulmonary hypertension patients for diagnosis, disease staging or drug discovery. Applicant's earlier invention, described in U.S. Pat. No. 5,406,959, describes an endoarterial biopsy catheter that has demonstrated its safety and effectiveness in normal canines (Rothman, Mann et al., 1996), canines with experimentally-induced pulmonary hypertension (Rothman, Mann et al., 1998), and canines with single-sided lung transplant rejection (Rothman, Mann et al., 2003). Preliminary studies have also demonstrated the safety and efficacy of a catheter-based method to obtain endovascular samples from a porcine model of PAH.

Percutaneously-obtained pulmonary endoarterial biopsy samples were found to be of sufficient quantity and quality for porcine whole genome mRNA microarray analysis and microRNA analysis. Whole genome microarray analysis revealed time-sensitive variations in gene expression values as PAH progressed in the subject animal model. Genes previously shown to be associated with PAH displayed changes characteristic of the disease, and genes previously unassociated with PAH also displayed expression level dysregulation. These findings raise the possibility that the endoarterial biopsy catheter combined with microarray analysis may provide a valuable platform for the discovery of novel drug and biomarker targets in pulmonary hypertension and a platform to deliver individualized pharmacotranscriptomics.

MicroRNA analysis revealed pressure sensitive changes in microRNA expression. As our surgical shunt model of pulmonary hypertension progressed from a high flow low pressure (HFLP) manifestation to a high flow high pressure (HFHP) manifestation, different microRNAs became dysregulated either increasing or decreasing in expression relative to our baseline normal values.

Most new therapies promise to focus on arresting either the endothelial apoptosis that characterizes early PAH (angiopoetin-1 & endothelial nitric oxide synthase cell-base gene transfer (Zhao et al 2003; 2005), caspase inhibitors (Taraseviciene-Stewart et al 2001)) or the smooth muscle cell proliferation typical of late PAH (dichloroacetate (McMurtry et al 2004), simvastatin (Nishimura et al 2003), sidenafil (Wharton et al 2005), imatinib (Schermuly et al 2005), anti-survivin (McMurtry et al 2005), K+ channel replacement gene therapy (Pozeg et al 2003)).

Before administering therapies, however, it would be extremely valuable to determine which genes are dysregulated in each PAH patient at any stage of their individual disease progression. Without knowing what genes are aberrant during any point in the patient's disease course, targeted therapies may miss the mark in some patients. Life threatening side effects may emerge if the wrong cells, at the wrong time, are encouraged to die or proliferate in patients with compromised pulmonary vascular health.

A powerful method for determining the gene expression levels of thousands of genes simultaneously are DNA microarrays. Initially used for the classification of cancers that were difficult to discriminate histologically (Golub et al 1999, Bhattacharjee et al 2001, and Ramaswamy et al 2001), microarrays have been more recently applied to PAH (Geraci et al 2001). PAH microarray studies have been performed on whole lung homogenates in humans (Fantozzi et al 2005) and rats (Hoshikawa et al 2003), surgically-dissected pulmonary arteries in pigs (Medhora et al 2002), laser-microdissected pulmonary arteries in rats (Kwapiszewska et al 2005), and mononuclear peripheral blood in humans (Bull et al 2004). These studies have been performed to discover potentially novel PAH disease pathways, biomarkers, therapeutic targets and patient classification gene expression profiles.

To advance PAH microarray studies into practical clinical use, tissue procurement methodologies are required that do not require surgical explant or postmortem procurement, and peripheral blood has thus far proven to be inadequate to discriminate gene expression signatures between subgroups of PAH patients (Bull et al 2004; Bull et al 2007). To take advantage of the full power of microarray technologies in PAH patients, a safe and effective minimally invasive means for the repeat procurement of endovascular samples from living PAH patients is required.

The present invention provides for the use of a novel interventional catheter, an endoarterial biopsy catheter, to obtain serial biopsy specimens from hypertensive pulmonary vessels for analysis. The ability to procure endothelial and smooth muscle samples in a minimally invasive manner will allow physicians to use microarray profiling and other techniques to classify patients upon initial presentation according to their gene expression signatures, prescribe therapies that target genes empirically found to be dysregulated in each individual patient, and monitor and adjust PAH patient therapy according to subsequent biopsy findings. A greater understanding of the complex molecular pathways underlying each patient's PAH should enable more precise diagnosis and the delivery of more effective therapies. Also of importance is the ability to discover new uses for existing drugs as well as discovering new drug targets.

Individualized pharmacotranscriptomics based on endoarterial biopsy and microarray analysis represents a reasonable choice for researchers struggling with the complexities and contradictions of PAH and other vascular diseases. The huge literature generated from in vitro and animal studies falls short, at times, in addressing the actual facts of patient health. Many commentators describe this dilemma as the “bench-to-bedside gap”, where in vitro and animal laboratory data fails to model human disease circumstances (Aird, 2004). Bridging that gap through catheter-based access to the vasculature in a model that recapitulates the clinical and histopathological manifestations of a form of human pulmonary hypertension will likely enable closer correlations between animal studies and patient care, and serve as a model for other vascular-based diseases such as atherosclerosis, congestive heart failure, sickle cell disease, organ transplant rejection, connective tissue diseases, chronic obstructive pulmonary disease, pulmonary embolism, asthma, systemic inflammatory response, battlefield trauma, cancer, sepsis and acute respiratory distress syndrome. There is a need in the art to provide data from gene expression analyses in order to target novel candidates for use in treating or preventing PAH.

SUMMARY OF THE INVENTION

One aspect of the present invention provides for methods of treating an individual suffering from a vascular-related disease comprising the steps of:

a) obtaining a biopsy sample from the individual's pulmonary artery;

b) analyzing gene expression levels of the biopsy sample from the pulmonary artery of the individual and a non-diseased control;

c) comparing the gene expression levels between the biopsy sample from the pulmonary artery of the individual and the non-diseased control;

d) identifying at least one gene from step c) that is upregulated or downregulated in the biopsy sample based on the non-diseased control;

e) obtaining gene products from the genes identified in step c); and

f) selecting pharmaceutical agents which are known inhibitors of the gene products from the at least one upregulated gene or known promoters of the gene products from the at least one downregulated gene. An additional aspect to the present invention provides for the pharmaceutical agents selected for administration to the individual suffering from the vascular-related disease. In yet another aspect, the individual is categorized based on progression of the vascular-related disease, with the treatment being based on the timing of the disease.

Another aspect of the present invention provides for a means of comparing varying levels of gene expression based on an animal model for pulmonary arterial hypertension. In a preferred embodiment, the genes expressed in the animal model are genes found to be either upregulated or downregulated. In a more preferred embodiment, the upregulated or downregulated genes are time-dependent based on the time after exposure to the PAH.

Another aspect of the present invention provides for methods of identifying genes involved in the pathway of PAH based on differential gene expression studies in a time-dependent animal model for PAH. In one embodiment, the genes are compared to other known genes which are upregulated or downregulated in the known PAH pathway.

Yet another aspect of the present invention provides for methods of diagnosing a vascular-related disease in an individual comprising the steps of:

a) identifying at least one gene that is upregulated or downregulated in the vascular-related disease comprising the steps of:

-   -   1) obtaining a biopsy sample from the individual's pulmonary         artery during progression of the vascular-related disease;     -   2) obtaining a pulmonary artery sample from a non-diseased         control;     -   3) extracting RNA from the samples in steps 1) and 2);     -   4) obtaining gene products from the RNA extracted in step 3);         and     -   5) comparing gene expression levels from the biopsy sample with         the non-diseased control, and

b) associating the genes upregulated in the biopsy sample with an inhibitor of the gene products for administration to the individual and genes downregulated in the biopsy sample with a promoter of the gene products for administration to the individual.

Another aspect of the present invention provides for methods of treating an individual having a vascular-related disease by targeting microRNAs comprising the following steps:

a) assessing a stage of the vascular-related disease in the individual;

b) identifying whether microRNAs are upregulated or downregulated;

c) selecting the microRNAs to target based on the stage of the vascular-related disease and whether the microRNAs are upregulated or downregulated; and

d) administering an agent known to inhibit an upregulated microRNA or an agent known to promote a downregulated microRNA to the individual. A variation of this embodiment provides for the stage of the vascular-related disease being based on flow rates and blood pressure within an artery of the individual.

Another aspect of the present invention provides for methods of therapeutically targeting microRNA dysregulated in PAH comprising the steps of:

-   -   (a) obtaining a biopsy sample from the pulmonary artery during         the progression of PAH;     -   (b) obtaining a pulmonary artery sample from a non-diseased         control;     -   (c) extracting RNA from the artery samples;     -   (d) converting the RNA to cDNA;     -   (e) comparing levels of microRNA expression at the two differing         times;     -   (f) identifying microRNA dysregulated in PAH relative to         baseline; and     -   (g) inhibiting upregulated microRNA or promoting downregulated         microRNA identified in PAH biopsies.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a surgical shunt model of PAH and its association with congenital heart disease (CHD).

FIG. 2 depicts the endoarterial biopsy procedural configuration.

FIG. 3 depicts biopsies: normal vessels at baseline, hypertensive LPA at 7, 21, 60 and 180 days post shunt.

FIG. 4 depicts GeneSpring downstream analysis of microarray data.

DETAILED DESCRIPTION OF THE INVENTION

The model described in the present invention is surgically-induced PAH in pigs. Our model mimics human Eisenmenger syndrome (a form of PAH related to congenital heart malformation) in both symptoms and pathology (Corno et al 2003). The size of the animals makes the pulmonary vessels available to the catheter, providing a ready transition to human clinical use. And finally, the commercial availability of whole genome porcine microarrays (Bai et al 2003) makes the species ideal for our purposes in the study, and renders the use of cross species microarrays unnecessary (Medhora et al 2002).

By obtaining pulmonary endovascular samples at early, intermediate and late time points in PAH progression, and analyzing these samples using porcine whole genome microarrays, a time-sensitive microarray based map of the underlying molecular biology of PAH may be obtained. Improved knowledge of the molecular mechanisms underlying PAH progression can lead to the identification of stage-specific biomarkers, new therapeutic targets for drug intervention, and novel signaling pathways involved in the pathogenesis of PAH. These novel target genes can then be validated using quantitative PCR and immunohistochemical stains on porcine endoarterial biopsy samples procured concurrently. At the same time, the combination of minimally invasive endoarterial biopsy and whole genome microarray analysis can serve as an animal model for subsequent studies in PAH patients.

The following examples provided in this disclosure provide a profile gene expression in pulmonary hypertensive pigs by surgical anastomosis of the left pulmonary artery to the descending aorta. Endoarterial biopsy samples are collected from animals with a surgical shunt model of pulmonary hypertension at multiple time points over a 6-month time course. Gene expression analysis of the biopsy samples was performed on porcine microarrays. Microarray analysis was performed to detect dysregulated genes previously unassociated with PAH, discover novel biomarkers of pulmonary hypertension and novel targets for therapeutic intervention and advance knowledge of the molecular mechanisms of pulmonary hypertension. These studies will also help validate a new platform for PAH diagnosis and drug discovery, endoarterial biopsy and microarray analysis, for eventual clinical practice.

EXAMPLES Example I: Construction of a Microarray-Based Map of Changes in Gene Expression During the Progression of PAH and the Identification of Novel Therapeutic Candidates

In an animal model of PAH created by Antonio Corno and colleagues, pigs undergo surgery that redirects systemic circulation into the left pulmonary artery mimicking pulmonary hypertension secondary to congenital heart disease. The surgery elevates PA pressure and creates the same hemodynamic conditions that PAH patients experience. The present study investigates how the elevated pressure remodels the pulmonary vasculature. In Corno's studies, histology on necropsy confirmed intimal hyperplasia in the pulmonary arteries, evidence that the surgical shunt surgery described will cause endovascular remodeling (Corno et al 2003).

Biopsy Extraction and Surgery Protocol

20-30 kg Yucatan Micropigs (Sus scrofa, Yucatan micro breed) underwent surgical anastomosis of the left pulmonary artery to the descending aorta, resulting in left pulmonary arterial hypertension of at least systemic levels. Animals are penned in the laboratory for no less than one week prior to surgery and fed normal chow. On surgery day, animals were premedicated with 20 mg/kg intramuscular ketamine and 0.1 mg/kg intramuscular midazolam. After 0.25 mg of intramuscular atropine, anesthesia was induced with 1 mg/kg intravenous midazolam and 0.1 mg/kg intravenous fentanyl and maintained with 0.1 mg/kg/hr intravenous pancuronium bromide. Pigs were ventilated with an inspired oxygen fraction (FiO2) of 0.4, a tidal volume of 15 ml/kg, and a respiratory rate of 12 breaths/minute. One gram of intravenous cefazolin was given before and 2 hours after the surgical procedure. Surgical and catheter procedures were performed under general anesthesia with endo-tracheal intubation. Sedation medications and anesthetics were administered by an anesthesiologist. Intra-cardiac and intravascular pressures, EKG, and blood oxygen saturations were monitored continuously.

Under sterile conditions (the thoracic area was shaved and prepared with betadine, a left thoracotomy was performed through the fourth intercostal space, about 5 centimeters, to expose the great arteries. The main pulmonary artery (MPA) and its branches were identified and freed from surrounding tissue. Two clamps were placed on the proximal left pulmonary artery (LPA). The proximal LPA was sutured closed, using prolene, and the distal LPA was sutured end to side in a clamped region in the descending aorta (FIG. 1), using cardiovascular prolene. Pieces of LPA endoarterial tissue were taken for histology. The clamps were removed and an IV dose of 1 mg/kg Furosemide immediately given. Hemostasis was obtained with sutures and cautery. Direct needle blood pressures were recorded in the main pulmonary artery and in the newly anastomosed left pulmonary artery. The chest was closed with sutures, both subcutaneous and cutaneous layers, using prolene and surgical wire. The animals then were weaned from anesthesia and mechanical ventilation. Postoperative analgesia was provided with morphine four times a day and a 1-2 mg/kg dose from 0.25% solution of IV Bupivacaine, a local anesthetic. A circulating warming blanket was used during surgery and recovery.

Endoarterial biopsies were performed at baseline prior to surgery to obtain unaffected tissue, and at post-shunt timepoints to obtain hypertensive biopsy samples (FIG. 2). Follow up endoarterial biopsy procedures were scheduled 7, 21, and 180 days after surgery. On each catheterization day, animals were premedicated with 10 mg/kg of IV propofol, were intubated and ventilated at a rate of 12 breaths/min and were maintained under anesthesia with 1.5% halpthane. A femoral artery line was placed for monitoring. To obtain biopsies from the hypertensive left lung, an 8F introducer is placed in a carotid artery, and a 7F endhole catheter is advanced into the aorta. An angiogram is performed to visualize the LPA-aortic anastomosis. The 7F endhole catheter is then threaded through the anastomosis with X-ray fluroscopic guidance. An angiogram of the hypertensive left pulmonary vascular tree is then performed, and the catheter is advanced to the distal pulmonary artery selected for biopsy. A 0.038 in, 260 cm extra stiff Amplatz exchange guide wire will then be passed through the end-hole catheter. The end-hole catheter was exchanged for a long flexible 8F introducer sheath that is adapted with a radio opaque band at the distal end and shaped to conform to the vascular pathway. A 7F angiographic catheter was advanced through the sheath in to a 2.5 mm to 3.0 mm distal pulmonary artery branch, where an angiogram was obtained. The angiographic catheter will serve as a guide to advance the stiff sheath into a small vessel targeted for biopsy and will then be exchanged for the endoarterial biopsy catheter.

The endoarterial biopsy catheter has an external diameter of 2.5 mm and is composed of two flexible polymeric tubes that slide relative to each other. The inner tube has a stainless steel distal end with a beveled opening that is designed to accommodate arterial tissue. A vacuum is coupled to the inner tube and channeled to the beveled opening. The outer tube terminates in a stainless steel cutting tube. The proximal ends of the two tubes are with a spring powered operating mechanism. To obtain the biopsy sample a vacuum is transmitted to the beveled opening of the inner tube, causing a tissue sample to be drawn in. The outer tube is then advanced over the inner tube, severing the tissue sample. With this design, the area of artery contacted by the outer periphery of the beveled opening is larger than the inner aperture connected to the vacuum, this maintaining the tissue sample with its orientation preserved. After each biopsy, the catheter was removed and the tissue sample was placed in the appropriate solution for further processing and analysis. After the biopsy procedures were completed, repeated angiograms were obtained to assess the degree of vascular injury. At the end of the procedure, the biopsy catheter and introducer sheath were removed and hemostasis was obtained by surgical repair of the carotid artery. The animals will then be weaned from anesthesia and mechanical ventilation. Postoperative analgesia was provided with morphine four times a day and or fentanyl patches and non-steroidal anti-inflammatory drugs four times a day.

Tissue Processing

For microarray analysis, biopsy samples are placed in a test tube containing RNAlater (Qiagen), flash frozen in dry ice, and kept frozen until RNA extraction. Additional samples are preserved in formalin, OCT freezing solution, or Bouin's solution for subsequent immunohistochemical and quantitative PCR analysis.

Porcine Genome Arrays

The Affymetrix GeneChip® Porcine Genome Array provides comprehensive coverage of the Sus scrofa transcriptome. The array contains 23,937 probe sets that interrogate approximately 23,256 transcripts from 20,201 Sus scrofa genes.

The sequence information for this array was selected from public data sources including UniGene Build 28 (August 2004), GenBank® mRNAs up to Aug. 24, 2004, and GenBank® porcine mitochondrial and rRNA sequences. Probe sets consist of up to eleven probe pairs. The array format consists of eleven micron features synthesized on the 100 format.

RNA Extraction from Endoarterial Biopsy Samples

RNA was prepared from fresh frozen endoarterial biopsy samples in a segregated laboratory, specially prepared and cleaned regularly to destroy nucleases. Specimens were homogenized using QIAshredder columns (Qiagen, Valencia, Calif.) utilized in a FastPrep FP120 Homogenizer (Thermo Electron Corporation, Waltham, Mass.). RNA was isolated using RNeasy Mini columns (Qiagen, Valencia, Calif.) as per manufacturer's protocol. All total RNA was eluted in nuclease free water, and quantity was established by UV spectrophotometer. Final RNA integrity was evaluated by capillary electrophoresis on the Agilent 2100 Bioanalyzer (Agilent, Palo Alto, Calif.).

Gene Expression

Before target production, the quality and quantity of each RNA sample was assessed using a 2100 BioAnalyzer (Agilent). Target was prepared and hybridized according to the “Affymetrix Technical Manual”. Total RNA (ug) was converted into cDNA using Reverse Transcriptase (Invitrogen) and a modified oligo (dT)24 primer that contains T7 promoter sequences (GenSet). After first strand synthesis, residual RNA was degraded by the addition of RNaseH and a double-stranded cDNA molecule was generated using DNA Polymerase I and DNA Ligase. The cDNA will then be purified and concentrated using a phenol:chloroform extraction followed by ethanol precipitation. The cDNA products will then be incubated with T7 RNA Polymerase and biotinylated ribonucleotides using an In Vitro Transcription kit (Enzo Diagnostics). One-half of the cRNA product was purified using an RNeasy column (Qiagen) and quantified with a spectrophotometer. The cRNA target (20 ug) was incubated at 94° C. for 35 minutes in fragmentation buffer (Tris, MgOAc, KOAc). The fragmented cRNA was diluted in hybridization buffer (MES, NaCl, EDTA, Tween 20, Herring Sperm DNA, Acetylated BSA) containing biotin-labeled OligoB2 and Eukaryotic Hybridization Controls (Affymetrix). The hybridization cocktail was denatured at 99° C. for 5 minutes, incubated at 45° C. for 5 minutes and then injected into a GeneChip® cartridge. The GeneChip® array was incubated at 42° C. for at least 16 hours in a rotating oven at 60 rpm. GeneChips® were washed with a series of nonstringent (25° C.) and stringent (50° C.) solutions containing variable amounts of MES, Tween20 and SSPE. The microarrays will then be stained with Streptavidin Phycoerythrin and the fluorescent signal was amplified using a biotinylated antibody solution. Fluorescent images were detected in a GeneChip® Scanner 3000 and expression data was extracted using the GeneChip® Operating System v 1.1 (Affymetrix). All GeneChips® were scaled to a median intensity setting of 500. Gene expression levels were compared between biopsy samples taken from the control distal pulmonary vasculature (baseline LPA and RPA) and PAH distal pulmonary arteries (surgical shunt LPA).

Gene Expression Analysis

After RNA preparation, array hybridization and scanning of the Porcine GeneChips® exactly as recommended by Affymetrix, the data produced are processed using the Affymetrix tools in the R-Bioconductor package called /Affy/. This tool set allows for various probe level analyses of the data as well as probe level quality control. The MASS algorithm was used, taking into account both the MM and PM probe data, and generating “Present” or “Absent” calls for each gene on each chip. If boxplots of the porcine probe level data reveal that any of the hybridizations are of low quality, the data from these chips was removed from any downstream analysis. MASS with the non-linear Quantiles normalization (Affy package /normalize.quantiles)/ was used with this data set to produce data almost free of artificial correlations. The Present/Absent calls are also used to remove from the analysis the genes that were never expressed in any of the samples examined (this is analogous to using a P-value for gauging a gene's data quality on a chip, and then filtering).

Based on the first dozen chips processed, after normalization and quality control ˜19,000 genes were moved on to the next stage of the analysis. The commercial package GeneSpring was used to assess differential gene expression and perform tests using clustering algorithms. Thus far, hierarchical clustering has revealed that the time-point replicates have the greatest similarity to one another.

Gene expression fold changes for 7, 21 60 and 180 days post-surgery relative to baseline were then loaded into GSEA (gene set enrichment analysis) or specially written PERL scripts which carry out KS (Kolmogorov-Smirnov) statistical analysis in order to identify novel therapeutic candidates.

Novel Therapeutic Identification

During PAH the best therapeutic targets are those which are upregulated as the disease state progresses. Thus drugs which are known to counter the action of any upregulated genes and their products would be of the greatest potential therapeutic value. Therefore, lists of upregulated genes were then matched to drugs which target their gene products.

In addition, many drugs interact with multiple targets in the body's tissues. Lists of the targets (called genesets) for each of ˜2000 characterized drugs were obtained from the literature and online databases. These genesets were then used to search for drugs which would be most likely to have therapeutic value in PAH.

This was done by using KS statistics which computes the Kolmogorov-Smirnov score for a geneset for a particular drug within an ordered list. The KSscore task is used to examine the enrichment of a set of genes at the top of an ordered list. The KS score is high when the tags appear early (i.e. near the top) of the ordered list. The significance of the KS score for a particular test may be examined by computing KS scores for multiple sets of X query genes selected at random from the dataset (note that the KS score is not independent of the number of members of the query gene set). Using this approach we were able to identify in our messenger RNA expression dataset drugs which are currently used as therapeutics for PAH (see FIG. 1A). Importantly, using the same approach we were also able to identify additional potential therapeutics, within the existing pool of characterized drugs. This process identified existing drugs as novel therapeutics for PAH.

Example II: Gene Expression Analysis from Porcine Animal Model Data Gene Expression Analysis

The porcine studies indicate that single endoarterial biopsy samples obtained in the porcine model of surgical shunt PAH contain sufficient RNA for microarray analysis, as we were able to analyze the mRNAs in whole genome porcine microarrays. We obtained endoarterial biopsies and measured pulmonary arterial pressure (PAP) at baseline prior to surgery, and at approximately 7, 21, 60 and 180 days post-PAH surgery from several animals. Porcine whole genome expression values were obtained for biological replicates with 2 samples from each time point. These replicates produced 5 sets of high quality replicated expression data (baseline, day 7, day 21, day 60 and day 180; see Table 1 for PAP data). Downstream data analysis was carried out using commercial (Ingenuity; GeneSpring) and free/open source software (R; Bioconductor; GSEA).

Mean expression values were obtained for each gene by averaging the gene expression values of the two biopsies at each timepoint. The resulting gene expression mean values were used to calculate fold changes between day 7, 21, 60 and day 180 gene expression relative to baseline.

Validity of the model was confirmed by examining the gene expression changes for selected genes previously found to be dysregulated in PAH (Table 2). Endothelin 1 and protein-tyrosine kinase Tie2 both displayed upregulation in accordance with explanted tissue from IPAH transplant recipients (Dewatcher et al 2006), and platelet-derived growth factor receptor alpha, serotonin receptors 2B and 1D, calmodulin, transcription factor STAT5b, voltage-dependent anion channels 1, 2 and 3, and RAS p21 protein activator 1 also increased in our model while tumor necrosis factor and plasminogen activator inhibitor-1 were found to be downregulated in our model in a similar fashion with IPAH explant tissue results (Fantozzi et al 2005). Survivin was upregulated in our model in a similar fashion to published findings (McMurtry et al 2005), and FYN and VAV-1 oncogenes, requiem homolog, inward rectifier K+ channel, and chloride channel 1 also increased while DEAD/H box polypeptide 3 and angiopoietin 1 displayed decreased expression in agreement with patient findings (Geraci et al 2001). We also observed decreased expression of peroxisome proliferator-activated receptor gamma (Ameshima et al 2003), and downregulated vascular endothelial growth factor B (Louzier et al 2003) in correspondence with previous results. The concordance between genes previously found to be aberrant in published PAH studies and altered gene expression in our model attest to the validity and potential usefulness of gene expression data derived from endoarterial biopsies. The time dependent nature of gene expression dysregulation found in our model further demonstrates the utility of obtaining endoarterial biopsies at multiple time points in PAH progression.

While several of these genes have been previously associated with PAH (for example, KCBN1, CASP3, TLR4, IL1B, IL6, HMGCR, TOP1, FYN, PRKCA, EDNRB, PDGFRA, and HRT2B), several have not (for example, HSPE, YES1, CFTR, MAOA, MAOB, and CACND21), raising the intriguing possibility that known existing drugs that target upregulated genes previously unassociated with PAH may be effective in treatment of the disease.

Example III: Identification of Dysregulated microRNA During the Progression of PAH

Endoarterial biopsy samples percutaneously obtained during the progression of PAH were analyzed to correlate changes in microRNA expression to disease progression.

microRNA Expression Data Analysis

Data analysis was done in three stages. First, expression intensities were calculated for each miRNA probed on the array for all hybridizations (12 in total) using illumina's Beadstudio Version 3.0 software. Second, intensity values were quality controlled and normalized: quality control was carried out by using the illumina Beadstudio detection P-value set to <0.05 as a cutoff. This removed miRNAs which were effectively absent from the arrays (that is, were never detected). After this step, the initial 1145 miRNAs were reduced to 1094. All the arrays were then normalized using the normalize.quantiles routine from the Affy package in Bioconductor. This procedure accounted for any variation in hybridization intensity between the individual arrays

Finally, these normalized data were imported into GeneSpring and analysed for differentially expressed miRNAs. The groups of biological replicates were described to the software and significantly differentially expressed genes determined on the basis of Welch t-tests and fold difference changes in expression level. The determination of miRNA targets genes was done using a publicly available database of miRNA target sequences and a specially written PERL programming script.

miRNA Pressure Related Analysis

The data was also looked at to reflect the stages of the disease (based on blood pressure and flow rates), as opposed to the time point or the individual pigs. Three groups were defined (1) Normal (baseline); (2) High Flow Low Pressure ‘HFLP’ and (3) High Flow High Pressure ‘HFHP’ (see Table 11). The groups were compared back to the baseline and the statistically significantly differentially regulated miRNAs determined (Tables 12, 13, 14 & 15).

Using illumina microRNA expression microarrays, fluctuations in the level of expression of ˜1200 microRNAs were determined during the onset and progression of PAH. Porcine and Homo sapiens miRNA sequences are very often highly conserved. Expression comparisons were done on a timepoint basis, taking in account the available replicates and the statistical significance of the expression changes. The data was also looked at to reflect the stages of the disease (based on blood pressure and flow rates), as opposed to the time point or the individual pigs. Three groups were defined (1) Normal (baseline); (2) High Flow Low Pressure ‘HFLP’ and (3) High Flow High Pressure ‘HFHP’. The groups were compared back to the baseline and the statistically significantly differentially regulated miRNAs determined.

Finding Micro RNAs with Potential as Therapeutic Targets

The messenger RNA expression data set was analysed looking for expression changes in sets of genes with known target sites for particular miRNAs. miRNAs are known to negatively regulate gene expression at the level of translation by binding to upstream regions of mRNA and blocking events required for translation of the mRNA into protein. This was again done using Gene Set Enrichment Analysis (GSEA) and the publicly available miRNA genesets. “Cross-talk” is seen between the messenger RNA gene expression changes and the microRNA expression changes. The messenger RNA expression analysis directly revealed the differential expression of groups of genes competent to be regulated by these miRNA.

Example IV: Personalizing Therapeutic Regimens for Vascular-Based Diseases

The use of gene expression data to shape individual drug therapies has been postulated as the next phase in personalized medicine. The bioinformatic processing of an individual's gene expression data can be used to generate a ranked list of therapies suitable for that individual. PAH disease pathology varies greatly over time, and is also likely to be specific for particular individuals. The analysis of the RNA in the PAH biopsy samples allows therapies to be tailored to the individual at that particular stage of the diseases progression.

The genes and biochemical pathways changing the most at the level of gene expression can be determined by comparing the PAH biopsy samples to a baseline control of normal healthy vasculature tissue. Observations show time-dependent extensive changes in gene expression with the progression of PAH. Known targets for approved PAH therapeutics can be seen Up-regulated in the diseased state.

Drug therapies can be ranked by using the known targets of drugs as genesets. These drug signature lists can then be used in a process such as Gene Set Enrichment Analysis, or KS statistics. KS Statistics returns a score for how well ranked a particular drug would be for a particular patient.

A drug is represented as the set of its known target genes; this can be in the dozens for some bioactive compounds. Genesets for ˜2000 drugs were assembled. KS Statistics yields a value (‘KS score’) representing the positional distribution of the set of query genes (here, the drug targets) within an ordered list of genes (genes induced in PAH). The ordered list is produced by looking at the fold change in a mRNAs expression between time X and the baseline, and sorting on this value. The gene with the greatest fold change is ranked as #1, second greatest fold change is ranked as #2, etc. KS score is computed in accordance with the Kolmogorov-Smirnov non-parametric rank statistic where X is the number of genes in the query gene set, Z is the number of genes in the ordered list, and Y=Z−X. A suitable baseline is generated using gene expression from artery samples from non-diseased controls. These samples can be obtained surgically, percutaneously or post-mortem.

This process can be repeated for all the PAH time points and the resulting table of KS scores for each drug hierarchically clustered. This reveals which drugs are potentially of the greatest therapeutic value for a patient.

This supports the idea of achieving personalized treatments for vascular-based diseases by generating individualized drug prescriptions based on the bioinformatic processing of gene expression data from endoarterial biopsy samples obtained from diseased arteries. Similarly, this enables personalized treatments for vascular-based diseases by generating lists of dysregulated microRNA from the bioinformatic processing of microRNA expression data from endoarterial biopsy samples from diseased arteries.

TABLE 1 Pulmonary arterial pressures obtained during endoarterial biopsy catheterization for biopsy samples used in microarray analysis. Pulmonary Arterial Pressure mmHg Biopsy Sample Systolic Diastolic Mean Baseline Pig #9 22 11 17 Baseline Pig #10 25 16 18 Day 21 Pig #2 95 66 82 Day 21 Pig #6 41 26 33 Day 60 Pig #6 87 59 74 Day 60 Pig #5 49 27 38

TABLE 2 Selected genes previously associated with PAH similarly dysregulated in the porcine model. Fold Fold Fold Fold Change Change Change Change Gene Day 7/ Day 21/ Day 60/ Day 180/ Symbol Name Baseline Day 7 Day 21 Day 60 Day 180 Base Base Base Base VAV1 vav 1 32.56 21.65 237.16 138.29 15.39 −1.50 7.28 4.25 −2.12 oncogene RASA1 RAS p21 73.23 388.68 280.27 704.56 361.25 5.31 3.83 9.62 4.93 protein activator 1 TIE2 protein- 20.92 2.59 32.46 702.68 218.34 −8.08 1.55 33.59 10.44 tyrosine kinase Tie2 FYN fyn proto- 43.33 180.38 404.77 531.03 166.17 4.16 9.34 12.26 3.83 oncogene VDAC1 voltage- 1176.57 2350.33 6629.76 3144.14 2277.10 2.00 5.63 2.67 1.94 dependent anion channel 1 PDGFRA platelet- 69.46 152.75 10.45 611.81 18.80 2.20 −6.64 8.81 −3.69 derived growth factor receptor alpha 5-HT2B serotonin 2B 49.96 19.03 166.45 142.91 488.77 −2.63 3.33 2.86 9.78 receptor KCNJ2 inwardly 389.66 83.23 1059.11 212.29 84.28 −4.68 2.72 −1.84 −4.62 rectifying potassium channel KIR6.1 5-HT1D serotonin 1D 14.17 42.48 8.32 61.48 4.95 3.00 −1.70 4.34 −2.86 receptor DPF2 requiem, 140.95 123.89 140.90 195.55 93.92 −1.14 −1.00 1.39 −1.50 apoptosis response zinc finger gene VDAC2 Voltage- 5683.09 2665.62 1620.37 4940.32 3643.38 −2.13 −3.51 −1.15 −1.56 dependent anion channel 2 STAT5B signal 469.40 571.47 1327.53 808.09 626.07 1.22 2.83 1.72 1.33 transducer and activator of transcription 5b AGPT angiopoietin 1 17.825026 50.240685 11.806807 70.12715 3.4479218 2.82 −1.51 3.93 −5.17 BIRC5 apoptosis 169.33 751.37 140.45 31.26 44.69 4.44 −1.21 −5.42 −3.79 inhibitor survivin VDAC3 voltage- 4092.99 750.86 5013.26 959.72 2018.55 −5.45 1.22 −4.26 −2.03 dependent anion channel 3 PLANH1 plasminogen 27760.742 43007.71 23685.375 28771.838 36086.305 1.55 −1.17 1.04 1.30 activator inhibitor I PPARG peroxisome 177.80 12.86 18.96 194.20 62.40 −13.83 −9.38 1.09 −2.85 proliferator- activated receptor gamma 2 CALM1 Calmodulin 3092.78 2436.23 867.25 1401.38 2252.81 −1.27 −3.57 −2.21 −1.37 APOE apolipoprotein 358.91 206.34 94.35 129.60 288.79 −1.74 −3.80 −2.77 −1.24 E

TABLE 3 Day 7 prescription. Fold Fold Fold Fold Change Change Change Change D 7/ D 21/ D 60/ D 180/ Gene Probe ID Name Base Base Base Base Symbol DRUGS Ssc.11018.1.A1_at Mitogen-activated protein 39.80 −5.02 −17.27 −20.43 MAPK14 SCIO-469, RO-3201195 kinase 14 Ssc.15986.1.S1_at Insulin receptor 29.28 −16.85 −17.70 −19.01 INSR insulin, insulin aspart, insulin glulisine, insulin lispro, insulin glargine Ssc.873.1.S1_at Cell division control protein 27.38 −2.37 −4.66 −7.76 CDC2 flavopiridol 2 Ssc.29928.1.A1_at Histone deacetylase 11 (HD11) 21.56 −3.17 −2.91 −10.50 HDAC11 tributyrin, PXD101, pyroxamide, vorinostat, FR 901228 Ssc.100.1.S1_at Tumor necrosis factor 18.41 −1.70 −9.62 −3.15 TNF adalimumab, etanercept, precursor (TNF-alpha) infliximab, CDP870, golimumab, thalidomide Ssc.19672.1.S1_at RAC-alpha serine/threonine- 17.77 1.25 −19.82 −2.11 AKT1 enzastaurin protein kinase Ssc.14475.3.S1_a_at Peroxisome proliferator 13.83 −9.38 1.09 −2.85 PPARG rosiglitazone, GI262570, activated receptor gamma pioglitazone, tesaglitazar, (PPAR-gamma) troglitazone Ssc.14326.1.A1_at Mitogen-activated protein 12.63 1.56 −1.80 −7.24 MAPK13 SCIO-469 kinase 13 Ssc.25843.1.S1_at Chloride channel protein 2 11.77 −17.04 −21.97 −9.92 CLCN2 lubiprostone (ClC-2 Ssc.16201.1.A1_at Metabotropic glutamate 10.79 −35.68 −33.34 −47.92 GRM7 fasoracetam receptor Ssc.11381.1.S1_at Interferon-alpha/beta receptor 10.45 8.08 2.61 −1.30 IFNAR1 interferon beta-1a, interferon alpha chain alfa-2b, interferon alfacon-1, PEG-interferon alfa-2a, interferon alfa-2a/ribavirin, pegintron, interferon beta-1b, IFNA2A Ssc.5371.1.S1_a_at DNA polymerase epsilon subunit 10.16 1.68 −1.37 −3.14 POLE2 gemcitabine B (DNA polymerase II subunit B) Ssc.14471.1.S1_at B-lymphocyte antigen CD19 9.54 3.30 −10.32 3.04 CD19 combotox, HD37-dgRTA, MT103 Ssc.24856.1.A1_at phosphodiesterase 11A; cyclic 9.36 −2.70 −3.68 −2.68 PDE11A dyphylline, nitroglycerin, nucleotide phosphodiesterase aminophylline, dipyridamole, 11A1 tolbutamide, tadalafil, theophylline, pentoxifylline Ssc.189.1.S1_at Diacylglycerol O- 9.16 −4.21 −36.07 −24.06 DGAT1 omacor acyltransferase 1 Ssc.16186.1.S1_at T-cell surface glycoprotein 9.00 3.12 2.12 −5.66 CD3E visilizumab, MT103, muromonab- CD3 epsilon CD3 Ssc.15601.1.A1_s_at Interleukin-1 beta precursor 8.18 4.65 −14.71 −2.84 IL1B IL-1 trap (IL-1 beta) Ssc.5538.1.S1_at Carbonic anhydrase II 8.09 1.39 −2.25 −1.35 CA2 methazolamide, (Carbonate dehydratase II) hydrochlorothiazide, (CA-II) (Carbonic anhydrase acetazolamide, C)] trichloromethiazide, dorzolamide, chlorothiazide, dorzolamide/timolol, brinzolamide, chlorthalidone, benzthiazide, sulfacetamide, topiramate Ssc.113.1.S1_at Interleukin-1 alpha (IL-1 8.01 −2.65 −1.59 −7.73 ILIA IL-1 trap alpha) Ssc.2895.1.S1_at Serine/threonine-protein 7.48 −2.02 −2.45 −1.81 AURKB AZD-1152 kinase Ssc.8219.1.A1_at Histone deacetylase 8 (HD8) 7.21 −2.18 −12.09 −29.63 HDAC8 tributyrin, PXD101, pyroxamide, vorinostat, FR 901228 Ssc.13473.1.A1_at Ceramide glucosyltransferase 7.13 −2.88 −4.17 −6.14 UGCG N- butyldeoxygalactonojirimycin, N-butyldeoxynojirimycin Ssc.14129.1.A1_at 4-aminobutyrate 6.91 2.56 −21.17 −3.35 ABAT valproic acid aminotransferase, mitochondrial (GABA transaminase) Ssc.15379.1.S1_at diacylglycerol O- 6.60 −1.51 −3.49 −2.13 DGAT2 omacor acyltransferase homolog 2; GS1999full Ssc.15830.1.A1_at Retinoic acid receptor beta 6.60 −3.28 −1.83 −1.10 RARB etretinate, adapalene, 13-cis- retinoic acid, tazarotene, acitretin, retinoic acid, 9- cis-retinoic acid, fenretinide Ssc.17928.1.A1_at helicase (DNA) B; helicase B 6.40 −2.65 −4.38 −1.06 HELB epirubicin Ssc.19673.1.S1_at T-cell surface glycoprotein 6.40 2.70 2.03 −11.77 CD3D visilizumab, MT103 CD3 delta Ssc.17222.1.A1_at mucin 1, transmembrane; 6.31 −6.10 −5.94 −13.48 MUC1 HuHMFG1 Ssc.55.1.S1_at Epidermal growth factor 6.09 −5.46 −4.68 −4.52 EGFR cetuximab, AEE 788, receptor panitumumab, BMS-599626, ARRY- 334543, XL647, canertinib, gefitinib, HKI-272, PD 153035, lapatinib, vandetanib, erlotinib Ssc.19059.1.A1_at Type-1 angiotensin II receptor 5.57 −2.57 1.50 −11.08 AGTR1 amlodipine/olmes artan (AT1) (AT1AR medoxomil, losartan/hydrochlorothiazide, valsartan/hydrochlorothiazide, candesartan cilexetil, olmesartan medoxomil, irbesartan, losartan potassium, telmisartan, eprosartan, candesartan cilexetil/hydrochlorothiazide, hydrochlorothiazide/irbesartan, eprosartan/hydrochlorothiazide, hydrochlorothiazide/telmisartan, hydrochlorothiazide/olmesartan medoxomil, valsartan Ssc.16162.1.S1_at 4-hydroxyphenylpyruvate 5.43 −8.93 −8.65 −3.84 HPD nitisinone dioxygenase Ssc.27603.1.S1_at Endothelin B receptor 5.30 −3.27 15.99 1.23 EDNRB bosentan, sitaxsentan, atrasentan Ssc.16333.1.A1_at Multidrug resistance protein 1 4.94 −2.99 −3.50 −22.89 ABCB1 XR9576, OC 144-093, valspodar Ssc.12769.1.A1_at Amiloride-sensitive cation 4.82 −13.74 −9.59 −10.72 ACCN1 amiloride, channel 1, neuronal amiloride/hydrochlorothiazide Ssc.17155.1.A1_at heparanase; heparanase-1 4.81 5.38 2.98 −1.83 HPSE heparanase inhibitor PI-88 Ssc.15933.1.S1_s_at Cytotoxic T-lymphocyte protein 4.76 −5.14 −6.63 −26.39 CTLA4 ipilimumab, ticilimumab 4 (Cytotoxic T-lymphocyte- associated antigen 4) (CTLA-4) (CD152 antigen) Ssc.15965.1.S1_at Inward rectifier potassium 4.68 2.72 −1.84 −4.62 KCNJ2 nicorandil, amiodarone channel 2 (IRK1) Ssc.26351.1.S1_at cAMP-specific 3′,5′-cyclic 4.67 4.99 3.61 −1.15 PDE4D dyphylline, nitroglycerin, phosphodiesterase 4D arofylline, tetomilast, L 869298, aminophylline, anagrelide, cilomilast, milrinone, rolipram, dipyridamole, L-826, 141, roflumilast, tolbutamide, theophylline, pentoxifylline, caffeine Ssc.15990.1.A1_at Retinoic acid receptor RXR- 4.42 −4.18 −18.45 −24.58 RXRA bexarotene, retinoic acid, 9- alpha cis-retinoic acid Ssc.2605.1.A1_at Protein farnesyltransferase 4.39 −2.62 −7.00 −2.74 FNTB lonafarnib, tipifarnib beta Ssc.30373.1.A1_at cGMP-specific 3′,5′-cyclic 4.27 1.52 2.34 4.09 PDE5A dyphylline, nitroglycerin, DA- phosphodiesterase 8159, aminophylline, sildenafil, dipyridamole, aspirin/dipyridamole, vardenafil, tolbutamide, tadalafil, theophylline, pentoxifylline Ssc.19233.1.S1_at Collagen alpha 2(IX) chain 4.23 −1.14 −22.83 −2.12 COL9A2 collagenase Ssc.1147.1.A1_at Lipoprotein lipase 4.05 −5.49 3.78 −8.08 LPL nicotinic acid, lovastatin/niacin Ssc.13160.1.A1_at Voltage-dependent L-type 4.03 −4.75 −1.11 −2.77 CACNA1F MEM-1003, mibefradil, calcium channel alpha-1F bepridil, nisoldipine, subunit isradipine, nicardipine Ssc.12748.1.A1_at Catechol O-methyltransferase, 4.03 −3.20 −5.82 −21.93 COMT carbidopa/entacapone/levodopa, membrane-bound form BIA-3-202, tolcapone, entacapone Ssc.24986.1.S1_at Aldehyde dehydrogenase 1A1 4.00 −3.76 −2.17 −9.20 ALDH1A1 disulfiram, chlorpropamide Ssc.15972.1.S1_at Peroxisome proliferator 3.83 −1.07 −2.73 −1.60 PPARD GW501516 activated receptor delta (PPAR-delta) Ssc.24509.1.A1_at Gamma-aminobutyric-acid 3.76 −1.28 −1.98 −1.23 GABRP alphadolone, sevoflurane, receptor pi subunit isoflurane, isoniazid, felbamate, etomidate, halothane, fluoxetine/olanzapine, eszopiclone, zolpidem, lorazepam, olanzapine, zaleplon, secobarbital, phenobarbital, pentobarbital, desflurane, methoxyflurane, enflurane Ssc.7176.1.A1_at C-X-C chemokine receptor type 3.74 10.91 8.15 1.68 CXCR4 JM 3100 4 (CXC-R4) ( Ssc.6570.1.S1_at Delta-aminolevulinic acid 3.71 −3.43 −3.05 −1.66 ALAD delta-aminolevulinic acid dehydratase] Ssc.17485.1.S1_at Guanylate cyclase soluble, 3.57 −38.82 −1.77 −7.04 GUCY1A2 nitroglycerin, isosorbide-5- alpha-2 chain mononitrate, isosorbide dinitrate, nitroprusside, isosorbide dinit rate/hydralazine Ssc.26200.1.S1_at Thyroid hormone receptor beta- 3.49 −1.56 7.96 2.52 THRB 3,5-diiodothyropropionic acid, 1 amiodarone, thyroxine, L- triiodothyronine Ssc.9595.1.S1_at Beta platelet-derived growth 3.48 −3.60 1.40 1.65 PDGFRB dasatinib, sunitinib, factor receptor axitinib, KRN-951, imatinib, sorafenib, becaplermin Ssc.108.1.S1_at Oxytocin receptor (OT-R) 3.44 −8.53 −16.69 −4.47 OXTR TT-235 Ssc.15801.1.A1_at Protein kinase C, beta 3.36 6.36 3.53 −4.98 PRKCB1 enzastaurin, ruboxistaurin Ssc.27928.1.S1_at Opioid growth factor receptor 3.34 −3.33 −2.89 −3.51 OGFR enkephalin, methionine (OGFr) Ssc.12791.1.A1_at 3-hydroxy-3-methylglutaryl- 3.27 2.77 1.77 −2.56 HMGCR aspirin/pravastatin, coenzyme A reductase (HMG-CoA lovastatin/niacin, reductase ezetimibe/simvastatin, amlodipine/atorvastatin, fluvastatin, cerivastatin, atorvastatin, pravastatin, simvastatin, lovastatin, rosuvastatin Ssc.7933.1.A1_at Cell division protein kinase 8 3.26 −1.63 −1.78 −3.05 CDK8 flavopiridol Ssc.11147.1.S1_at Aldehyde dehydrogenase, 3.18 1.13 2.00 −1.68 ALDH2 disulfiram, chlorpropamide mitochondrial (ALDH class 2) (ALDHI) (ALDH-E2) Ssc.19608.1.S1_at Retinoic acid receptor RXR- 3.15 −1.39 −1.73 −3.97 RXRG bexarotene, retinoic acid, 9- gamma cis-retinoic acid Ssc.29260.1.A1_at Granulocyte colony stimulating 3.15 −2.50 −4.36 −4.68 CSF3R pegfilgrastim, filgrastim factor receptor (G-CSF-R) (CD114 antigen)] Ssc.22797.1.S1_at DNA topoisomerase II, beta 3.15 −1.87 1.02 −2.91 TOP2B novobiocin, etoposide, CPI- isozyme 0004Na, pixantrone, becatecarin, elsamitrucin, AQ4N, BN 80927, tafluposide, mitoxantrone, norfloxacin, dexrazoxane, tirapazamine, TAS- 103, XK469, gatifloxacin, valrubicin, gemifloxacin, moxifloxacin, nemorubicin, nalidixic acid, epirubicin, doxorubicin, daunorubicin Ssc.16121.1.A1_at Corticotropin releasing factor 3.03 −4.50 −17.00 −4.36 CRHR1 Crh, CRA0165, CRA1001, receptor 1 SSR125543A Ssc.12630.1.A1_at Sodium/potassium-transporting 2.97 2.81 −7.30 −2.03 ATP1Al digoxin, omeprazole, ATPase alpha-1 chain ethacrynic acid, perphenazine Ssc.13254.1.A1_at Metabotropic glutamate 2.95 −15.40 −9.66 −3.57 GRM8 fasoracetam receptor 8 Ssc.30888.1.S1_at Voltage-dependent L-type 2.92 −2.72 1.90 −7.82 CACNA1D MEM-1003, mibefradil, calcium channel alpha-1D bepridil, nisoldipine, isradipine, nicardipine Ssc.9565.1.S1_at Interferon-gamma receptor 2.92 1.63 1.41 −1.23 IFNGR1 interferon gamma-1b alpha Ssc.15880.1.S1_at Cysteinyl leukotriene receptor 2.86 1.14 −2.12 −3.42 CYSLTR2 montelukast, zafirlukast 2 (CysLTR2) Ssc.2753.1.S1_at Serine/threonine-protein 2.77 −4.42 −7.50 −4.52 PLK1 BI 2536 kinase PLK1 Ssc.16123.1.A1_at cAMP-specific 3′,5′-cyclic 2.75 −3.97 −3.49 −1.46 PDE4A arofylline, tetomilast, L phosphodiesterase 4A 869298, anagrelide, cilomilast, milrinone, rolipram, L-826, 141, amrinone, roflumilast, pentoxifylline, caffeine Ssc.11383.1.A1_at Glutamate receptor 3 2.61 1.85 −1.87 −2.43 GRIA3 talampanel, Org 24448, LY451395, tezampanel Ssc.14403.1.S1_at Sodium/potassium-transporting 2.61 −1.95 −8.51 −6.43 ATP1A2 digoxin, omeprazole, ATPase alpha-2 chain ethacrynic acid, perphenazine Ssc.21754.1.A1_at Collagen alpha 1(VI) chain 2.57 −47.00 −5.79 −4.37 COL6A1 collagenase Ssc.6498.1.A1_at Mitogen-activated protein 2.41 −10.79 −5.78 −3.26 MAPK12 SCIO-469 kinase 12 (Mitogen-activated protein kinase p38 gamma) Ssc.16167.1.S1_at Rho-associated protein kinase 2.40 2.32 2.83 3.00 ROCK1 fasudil, Y-27632 1 Ssc.12781.1.A1_at Toll-like receptor 4 2.39 1.83 −1.52 −6.10 TLR4 TAK-242 Ssc.29366.1.A1_at DNA topoisomerase I 2.37 −2.30 −2.87 −10.72 TOP1 elsamitrucin, T 0128, CT-2106, BN 80927, tafluposide, TAS-103, beta-lapachone, irinotecan, topotecan, 9-amino-20- camptothecin, rubitecan, gimatecan, karenitecin Ssc.14485.1.S1_at Parathyroid 2.28 −1.62 −3.40 −6.83 PTHR1 teriparatide hormone/parathyroid hormone- related peptide receptor Ssc.12238.1.A1_at Cysteinyl leukotriene receptor 2.28 −1.73 −1.34 −6.96 CYSLTR1 zeneca ZD 3523, montelukast, 1 (CysLTR1) zafirlukast Ssc.3607.1.S1_at Interferon-alpha/beta receptor 2.28 4.65 1.11 −1.56 IFNAR2 interferon beta-1a, interferon beta chain alfa-2b, interferon alfacon-1, PEG-interferon alfa-2a, interferon alfa-2a/ribavirin, pegintron, interferon beta-1b, IFNA2A Ssc.2548.1.S1_at DNA polymerase epsilon p17] 2.27 1.93 −1.67 −1.21 POLE3 gemcitabine Ssc.19706.1.A1_at Mitogen-activated protein 2.25 −4.27 −2.31 −4.98 MAPK8 aplidine kinase 8 Ssc.15382.1.S1_at Cannabinoid receptor 2 (CB2) 2.22 3.48 −1.37 −4.69 CNR2 BAY 38-7271, delta-9- (CB-2) (CX5) tetrahydrocannabinol Ssc.4756.1.A1_at Adenosine A3 receptor 2.15 2.10 1.88 −1.81 ADORA3 adenosine, dyphylline, aminophylline, clofarabine, theophylline, caffeine Ssc.23261.1.A1_at Trifunctional purine 2.15 −3.54 −3.66 −5.67 GART LY231514 biosynthetic protein adenosine-3 Ssc.27293.1.A1_at Hypoxanthine-guanine 2.15 −1.16 1.63 −7.14 HPRT1 6-mercaptopurine, thioguanine, phosphoribosyltransferase azathioprine Ssc.14476.1.S1_at Interleukin-2 receptor alpha 2.07 −8.52 −8.73 −5.00 IL2RA LMB-2, daclizumab, basiliximab, aldesleukin, denileukin diftitox Ssc.27232.1.S1_at Succinate semialdehyde 2.06 1.12 −2.84 −5.73 ALDH5A1 valproic acid dehydrogenase, mitochondrial Ssc.10142.1.A1_at Dihydropyrimidine 2.06 2.17 1.13 −2.68 DPYD eniluracil dehydrogenase [NADP+] Ssc.1908.1.S1_at FKBP-rapamycin associated 1.99 1.13 −1.88 −1.46 FRAP1 AP23573, temsirolimus, protein (FRAP) tacrolimus, everolimus Ssc.204.1.S1_at Cytochrome P450 3A4 1.97 −3.35 2.16 −1.42 CYP3A4 ketoconazole Ssc.18459.1.S1_at Amiloride-sensitive sodium 1.97 −2.41 1.43 −1.93 SCNN1A triamterene/hydrochlorothiazide, channel alpha- amiloride, amiloride/hydrochlorothiazide, triamterene Ssc.24889.1.S1_at Arachidonate 12-lipoxygenase, 1.97 2.83 −1.18 −2.78 ALOX12 sulfasalazine, balsalazide, 5- 12S-type aminosalicylic acid, masoprocol, verteporfin Ssc.15748.2.S2_at T lymphocyte activation 1.95 −1.24 1.54 −3.12 CD80 abatacept antigen CD80 Ssc.5826.1.A1_at Macrophage colony stimulating 1.93 −4.97 −13.18 1.61 CSF1R sunitinib factor I receptor (CD115 antigen) Ssc.15822.1.S1_at Coagulation factor V 1.92 3.76 1.89 −1.75 F5 drotrecogin alfa Ssc.9262.1.A1_at Histamine H1 receptor 1.91 −4.10 −3.91 −1.86 HRH1 nitisinone Ssc.62.2.S1_a_at Interleukin-6 (IL-6) ( 1.89 −6.32 2.77 −1.04 IL6 tocilizumab Ssc.14258.1.S1_at Amyloid beta A4 protein 1.87 3.33 1.34 −1.02 APP AAB-001 Ssc.15878.1.S1_at Serine/threonine protein 1.85 3.22 3.62 −1.49 PPP3CA ISAtx-247, tacrolimus, phosphatase 2B pimecrolimus, cyclosporin A Ssc.19379.1.A1_at Voltage-dependent L-type 1.83 −1.34 1.07 −3.27 CACNA1C clevidipine, MEM-1003, calcium channel alpha-1C amlodipine/olmesartan subunit medoxomil, amlodipine/benazepril, diltiazem, verapamil, mibefradil, bepridil, enalapril/felodipine, amlodipine/atorvastatin, nisoldipine, isradipine, felodipine, nimodipine, nitrendipine, amlodipine, nicardipine, nifedipine, trandolapril/verapamil, diltiazem/enalapril Ssc.10215.1.A1_at High-affinity cAMP-specific 1.83 1.12 −8.48 −15.51 PDE8A dyphylline, nitroglycerin, and IBMX-insensitive 3′,5′- aminophylline, anagrelide, cyclic phosphodiesterase 8A milrinone, dipyridamole, tolbutamide, theophylline, pentoxifylline Ssc.20944.1.S1_at Carbonic anhydrase XIV 1.82 −3.49 −5.34 −12.64 CA14 methazolamide, hydrochlorothiazide, acetazolamide, trichloromethiazide, chlorothiazide, chlorthalidone, benzthiazide, sulfacetamide, topiramate Ssc.4125.1.A1_at Histone deacetylase 5 (HD5) 1.82 −4.64 −4.18 −2.74 HDAC5 tributyrin, PXD101, pyroxamide, vorinostat, FR 901228 Ssc.9272.1.S1_at Tumor-associated calcium 1.81 3.94 176.50 2.07 TACSTD1 tucotuzumab celmoleukin signal transducer 1 (EPCAM antigen) Ssc.6301.1.S1_at Aromatic-L-amino-acid 1.76 1.80 −4.91 −1.88 DDC carbidopa/entacapone/levodopa, decarboxylase carbidopa/levodopa, S(−)- carbidopa, L-dopa Ssc.15995.1.S1_at Potassium voltage-gated 1.74 −26.30 −13.45 −2.79 KCNE1 nicorandil, amiodarone, channel subfamily E member 1 azimilide Ssc.7581.1.A1_at FL cytokine receptor precursor 1.69 1.04 −1.81 1.01 FLT3 CHIR-258, sorafenib, lestaurtinib, CGP 41251 Ssc.26325.1.S1_at Cystic fibrosis transmembrane 1.60 −5.71 4.77 −8.99 CFTR SP 303 conductance regulator (CFTR) Ssc.19691.1.S1_at Platelet-activating factor 1.59 1.16 3.01 1.47 PLA2 G7 darapladib acetylhydrolase Ssc.24714.1.A1_at Excitatory amino acid 1.58 −2.29 −7.61 −3.45 SLC1A2 riluzole transporter 2 (Sodium- dependent glutamate/aspartate transporter 2) Ssc.22477.1.S1_at Collagen alpha 1(IV) chain 1.58 −5.08 −1.78 1.04 COL4A1 collagenase Ssc.227.1.S1_at Potassium-transporting ATPase 1.56 −5.89 −51.53 −15.60 ATP4B ilaprazole, TAK-390MR, beta tenatoprazole, AGN 201904, AR- H047108, esomeprazole magnesium, omeprazole, lansoprazole, amoxicillin/clarithromycin/lans oprazole, rabeprazole, pantoprazole Ssc.30147.1.A1_at Fibroblast growth factor 1.56 1.13 −1.05 −1.18 FGFR2 palifermin receptor 2 Ssc.9523.1.A1_at Methylated-DNA--protein- 1.55 −1.17 3.35 1.47 MGMT O6-benzylguanine cysteine methyltransferase Ssc.26466.1.A1_at Integrin beta-3 (CD61 antigen 1.55 −1.49 −4.11 −2.73 ITGB3 TP 9201, EMD121974, tirofiban Ssc.5592.1.S1_at Protein 1.49 −3.49 −2.81 −3.68 FNTA lonafarnib, tipifarnib famesyltransferase/geranylger anyltransferase type I alpha Ssc.17986.1.A1_at Poly [ADP-ribose] polymerase-1 1.47 −6.14 −4.64 −5.80 PARP1 INO-1001 Ssc.11051.1.S1_at Cell division protein kinase 4 1.44 −7.67 −4.96 23.75 CDK4 PD-0332991, flavopiridol Ssc.20818.1.S1_at Interleukin-2 receptor beta 1.43 6.35 −1.17 −5.23 IL2RB humanized MiK-Beta-1, chain aldesleukin, denileukin diftitox Ssc.16489.1.S1_at Interleukin-7 receptor alpha 1.42 2.34 1.86 −6.31 IL7R recombinant human interleukin- chain 7 Ssc.10287.1.A1_at Transforming growth factor 1.41 −4.54 1.43 1.67 TGFB2 AP-12009 beta 2 Ssc.14375.1.A1_at ribonucleotide reductase M2 B 1.40 −2.19 −5.17 −2.28 RRM2B triapine, hydroxyurea Ssc.16823.1.S1_at P2Y purinoceptor 12 (P2Y12) 1.38 1.19 1.41 1.11 P2RY12 prasugrel, AZD 6140 (P2Y12 platelet ADP receptor) (Ticagrelor), clopidogrel (P2Y(ADP)) Ssc.11164.1.A1_at DNA polymerase gamma subunit 1 1.37 −1.33 −3.67 −3.60 POLG stavudine, vidarabine, zalcitabine Ssc.10219.1.A1_at Excitatory amino acid 1.36 1.24 −3.38 −1.03 SLC1A6 riluzole transporter 4 Ssc.3815.1.S1_at RAC-beta serine/threonine- 1.35 −3.13 −3.28 −3.19 AKT2 enzastaurin protein kinase Ssc.19619.1.S1_at Proto-oncogene tyrosine- 1.35 −1.51 −3.32 −2.41 LCK dasatinib protein kinase LCK Ssc.2926.1.S1_at Heme oxygenase 2 1.34 −1.43 −4.13 −1.81 HMOX2 tin mesoporphyrin Ssc.11171.1.S1_at Adenosine deaminase 1.32 −2.04 −3.23 1.12 ADA pentostatin, vidarabine Ssc.16621.1.A1_at Excitatory amino acid 1.27 −7.18 −3.04 −8.29 SLC1A1 riluzole transporter 3 Ssc.11549.1.A1_at Dual specificity mitogen- 1.25 −33.67 −11.33 −6.48 MAP2K1 PD 0325901 activated protein kinase kinase 1 Ssc.6356.1.S1_at Ornithine decarboxylase 1.24 −1.36 −1.74 −1.84 ODC1 tazarotene, eflornithine Ssc.15999.1.A1_at Vascular endothelial growth 1.24 1.24 18.52 −11.02 KDR AEE 788 , sunitinib, AZD 2171, factor receptor 2 (VEGFR-2) pazopanib, XL647, CEP 7055, BMS-582664, KRN-951, vatalanib, sorafenib, vandetanib, pegaptanib Ssc.9669.1.S1_at Cell division protein kinase 5 1.21 −2.68 −17.06 −1.65 CDK5 flavopiridol Ssc.115.1.S1_s_at Heme oxygenase 1 1.18 −2.09 −3.40 −3.55 HMOX1 tin mesoporphyrin Ssc.17224.1.S1_at Toll-like receptor 8 1.17 6.49 3.13 −1.52 TLR8 resiquimod Ssc.8046.1.A1_at peptidylprolyl isomerase A 1.16 −1.08 1.39 1.26 PPIA N-methyl-4-Ile-cyclosporin isoform 1 Ssc.7297.1.S1_at Amine oxidase [flavin- 1.16 6.42 7.02 −1.13 MAOB safinamide, ladostigil, containing] B (MAO-B) rasagiline, selegiline, dextroamphetamine, procainamide, tranylcypromine, phenelzine, isocarboxazid, benzphetamine Ssc.28329.1.S1_at DNA polymerase beta 1.14 1.19 1.07 5.25 POLB nelarabine, clofarabine, stavudine, trifluridine, vidarabine, zalcitabine, entecavir Ssc.12202.2.S1_at Farnesyl pyrophosphate 1.12 −1.26 −2.68 −1.13 FDPS YM 529, alendronic acid, synthetase pamidronic acid Ssc.19700.1.S1_at Serine/threonine protein 1.11 1.13 1.34 1.09 PPP3CB ISAtx-247, tacrolimus, phosphatase 2B catalytic pimecrolimus, cyclosporin A subunit, beta Ssc. 8549.1.A1_at Guanylate cyclase soluble, 1.11 1.84 −2.00 −2.59 GUCY1A3 nitroglycerin, isosorbide-5- alpha-3 chain mononitrate, isosorbide dinitrate, nitroprusside, isosorbide dinitrate/hydralazine Ssc.15374.1.S1_at COL14A1 protein 1.10 −17.71 3.79 2.24 COL14A1 collagenase Ssc.15901.1.S1_at cGMP-inhibited 3′,5′-cyclic 1.10 −13.33 −3.16 −1.41 PDE3A dyphylline, nitroglycerin, phosphodiesterase A medorinone, aminophylline, cilostazol, dipyridamole, amrinone, tolbutamide, theophylline, pentoxifylline Ssc.16000.1.A1_at Vascular endothelial growth 1.08 −3.40 3.34 1.72 FLT1 sunitinib, axitinib, CEP 7055 factor receptor 1 Ssc.20987.1.S1_at Thrombopoietin receptor] 1.06 −1.58 −3.97 −5.87 MPL SB-497115 Ssc.11149.1.S1_at Carbonic anhydrase IX 1.04 −1.91 −1.33 −1.26 CA9 cG250, I 131 chimeric G250, Y 90 chimeric G250, methazolamide, hydrochlorothiazide, acetazolamide, trichloromethiazide, chlorothiazide, chlorthalidone, benzthiazide, sulfacetamide, topiramate Ssc.8726.1.A1_at Amidophosphoribosyltransferase 1.03 1.24 4.16 −1.11 PPAT 6-mercaptopurine, thioguanine, azathioprine Ssc.11406.1.A1_a_at Interleukin-1 receptor, type I 1.03 2.70 −2.44 1.42 IL1R1 anakinra Ssc.14506.1.S1_at DNA topoisomerase II, alpha 1.01 3.80 −1.18 −14.30 TOP2A novobiocin, etoposide, CPI- 0004Na, pixantrone, becatecarin, elsamitrucin, AQ4N, BN 80927, tafluposide, mitoxantrone, norfloxacin, dexrazoxane, tirapazamine, TAS- 103, gatifloxacin, valrubicin, gemifloxacin, moxifloxacin, nemorubicin, nalidixic acid, epirubicin, doxorubicin, daunorubicin

TABLE 4 Day 21 prescription. Fold Fold Fold Fold Change Change Change Change D 7/ D 21/ D 60/ D 180/ Gene Probe ID Name Base Base Base Base Symbol Drugs Ssc.23793.1.S1_at T-cell surface antigen CD2 −3.27 79.25 93.34 5.20 CD2 alefacept, siplizumab SscAffx.20.1.S1_at T-cell surface glycoprotein −2.19 14.07 10.96 3.62 CD3G visilizumab, MT103 CD3 gamma chain Ssc.19532.1.S1_at Guanylate cyclase soluble, −4.28 12.74 3.04 2.13 GUCY1B3 nitroglycerin, isosorbide-5- beta-1 chain mononitrate, isosorbide dinitrate, nitroprusside, isosorbide dinitrate/hydralazine Ssc.7176.1.A1_at C-X-C chemokine receptor type 3.74 10.91 8.15 1.68 CXCR4 JM 3100 4 (CXC-R4) (CXCR-4) (CD184 antigen). Ssc.2714.1.S1_a_at Proto-oncogene tyrosine- −4.26 9.56 12.54 3.93 FYN dasatinib protein kinase FYN Ssc.15739.1.S1_at Cytokine receptor common gamma −1.12 9.42 1.90 −1.28 IL2RG aldesleukin, denileukin chain (Interleukin- 2 diftitox receptor gamma chain) (IL-2R gamma chain) (CD132 antigen). Ssc.11381.1.S1_at Interferon-alpha/beta receptor 10.45 8.08 2.61 −1.30 IFNAR1 interferon beta-1a, interferon alpha chain alfa-2b, interferon alfacon-1, PEG-interferon alfa-2a, interferon alfa-2a/ribavirin, pegintron, interferon beta-1b, IFNA2A Ssc.10256.1.A1_at cAMP-specific 3′,5′-cyclic −1.89 6.74 2.20 2.44 PDE4B dyphylline, nitroglycerin, phosphodiesterase 4B arofylline, tetomilast, L 869298, aminophylline, anagrelide, cilomilast, milrinone, rolipram, dipyridamole, L-826, 141, roflumilast, tolbutamide, theophylline, pentoxifylline, caffeine Ssc.17224.1.S1_at Toll-like receptor 8 1.17 6.49 3.13 −1.52 TLR8 resiquimod Ssc.7297.1.S1_at Amine oxidase [flavin- 1.16 6.42 7.02 −1.13 MAOB safinamide, ladostigil, containing] B (Monoamine rasagiline, selegiline, oxidase) (MAO-B). dextroamphetamine, procainamide, tranylcypromine, phenelzine, isocarboxazid, benzphetamine Ssc.15801.1.A1_at Protein kinase C, beta 3.36 6.36 3.53 −4.98 PRKCB1 enzastaurin, ruboxistaurin Ssc.20818.1.S1_at Interleukin-2 receptor beta 1.43 6.35 −1.17 −5.23 IL2RB humanized MiK-Beta-1, chain (IL-2 receptor) aldesleukin, denileukin diftitox Ssc.12937.1.S1_at Presenilin 1 (PS-1) (S182 −14.09 6.21 2.48 3.79 PSEN1 (R)-flurbiprofen protein). Ssc.15932.1.S1_at Integrin alpha-V −6.15 5.79 2.94 3.14 ITGAV abciximab, CNTO 95, EMD121974 Ssc.26328.1.S1_at C-C chemokine receptor type 5 −2.53 5.61 3.25 1.29 CCR5 maraviroc, vicriviroc, SCH (CCR5) (CD195 antigen). 351125 Ssc.12845.1.S1_at Cell division protein kinase 6 −6.56 5.40 4.77 5.13 CDK6 PD-0332991, flavopiridol Ssc.17155.1.A1_at heparanase; heparanase-1 4.81 5.38 2.98 −1.83 HPSE heparanase inhibitor PI-88 Ssc.13460.1.A1_at Histone deacetylase 9 (HD9) −6.40 5.13 −1.79 5.72 HDAC9 tributyrin, PXD101, (HD7B) (HD7) pyroxamide, vorinostat, FR 901228 Ssc.24528.1.S1_at Angiotensin-converting enzyme −1.61 5.01 2.33 4.76 ACE pentopril, perindoprilat, amlodipine/benazepril, lisinopril/hydrochlorothiazide, benazepril, enalapril, perindopril, captopril, enalapril/felodipine, hydrochlorothiazide/moexipril, benazepril/hydrochlorothiazide, hydrochlorothiazide/quinapril, fosinopril/hydrochlorothiazide, captopril/hydrochlorothiazide, enalapril/hydrochlorothiazide, ramipril, moexipril, quinapril, lisinopril, enalaprilat, trandolapril, trandolapril/verapamil, diltiazem/enalapril, fosinopril Ssc.26351.1.S1_at cAMP-specific 3′,5′-cyclic 4.67 4.99 3.61 −1.15 PDE4D dyphylline, nitroglycerin, phosphodiesterase 4D arofylline, tetomilast, L 869298, aminophylline, anagrelide, cilomilast, milrinone, rolipram, dipyridamole, L-826,141, roflumilast, tolbutamide, theophylline, pentoxifylline, caffeine Ssc.15601.1.A1_s_at Interleukin-1 beta precursor 8.18 4.65 −14.71 −2.84 IL1B IL-1 trap (IL-1 beta) Ssc.3607.1.S1_at Interferon-alpha/beta receptor 2.28 4.65 1.11 −1.56 IFNAR2 interferon beta-1a, interferon beta chain alfa-2b, interferon alfacon-1, PEG-interferon alfa-2a, interferon alfa-2a/ribavirin, pegintron, interferon beta-1b, IFNA2A Ssc.20841.1.S1_at Proto-oncogene tyrosine- −1.13 4.37 −2.59 −1.93 SRC dasatinib, AZM-475271 protein kinase Src Ssc.11200.1.S1_a_at Proto-oncogene tyrosine- −1.15 4.28 −3.41 −1.18 ABL1 imatinib, temozolomide protein kinase ABL1 Ssc.22974.1.A1_at Metabotropic glutamate −1.05 4.28 −2.05 −5.66 GRM1 fasoracetam receptor 1 Ssc.7111.1.A1_at Ribonucleoside-diphosphate −13.13 4.08 1.37 1.67 RRM2 gemcitabine, triapine, reductase M2 chain hydroxyurea, fludarabine (Ribonucleotide reductase phosphate small chain) Ssc.9272.1.S1_at Tumor-associated calcium 1.81 3.94 176.50 2.07 TACSTD1 tucotuzumab celmoleukin signal transducer 1 (EPCAM antigen) Ssc.16160.1.S1_at T lymphocyte activation −1.55 3.88 −1.37 1.18 CD86 abatacept antigen CD86 Ssc.14506.1.S1_at DNA topoisomerase II, alpha 1.01 3.80 −1.18 −14.30 TOP2A novobiocin, etoposide, CPI- isozyme 0004Na, pixantrone, becatecarin, elsamitrucin, AQ4N, BN 80927, tafluposide, mitoxantrone, norfloxacin, dexrazoxane, tirapazamine, TAS- 103, gatifloxacin, valrubicin, gemifloxacin, moxifloxacin, nemorubicin, nalidixic acid, epirubicin, doxorubicin, daunorubicin Ssc.15822.1.S1_at Coagulation factor V 1.92 3.76 1.89 −1.75 F5 drotrecogin alfa (Activated protein C cofactor). Ssc.9034.1.A1_at Proteinase activated receptor −1.29 3.75 −1.40 1.37 F2R chrysalin, argatroban, 1 precursor (PAR-1) (Thrombin bivalirudin receptor) Ssc.15886.1.S1_at Apopain precursor (Caspase-3) −3.02 3.64 2.31 2.29 CASP3 IDN-6556 (CASP-3) Ssc.17518.1.S1_at Adenosine A1 receptor −3.16 3.44 −1.56 1.58 ADORA1 adenosine, dyphylline, aminophylline, clofarabine, theophylline, caffeine, tecadenoson Ssc.14258.1.S1_at Amyloid beta A4 protein 1.87 3.33 1.34 −1.02 APP AAB-001 precursor (APP) (ABPP) Ssc.14471.1.S1_at B-lymphocyte antigen CD19 9.54 3.30 −10.32 3.04 CD19 combotox, HD37-dgRTA, MT103 precursor (Differentiation antigen CD19 Ssc.15878.1.S1_at Serine/threonine protein 1.85 3.22 3.62 −1.49 PPP3CA ISAtx-247, tacrolimus, phosphatase 2B catalytic pimecrolimus, cyclosporin A subunit, alpha Ssc.21108.1.S1_at Complement C5 −17.35 3.21 618.80 9.28 C5 eculizumab Ssc.16186.1.S1_at T-cell surface glycoprotein 9.00 3.12 2.12 −5.66 CD3E visilizumab, MT103, muromonab- CD3 epsilon chain (T-cell CD3 surface antigen T3/Leu-4 epsilon chain) Ssc.24966.1.S1_at Purine nucleoside −3.34 3.12 3.46 −1.14 NP forodesine, 9-deaza-9-(3- phosphorylase (Inosine thienylmethyl)guanine phosphorylase) (PNP). Ssc.19873.1.S1_at Collagen alpha 1(XVII) chain −2.37 3.02 −1.55 2.18 COL17A1 collagenase (Bullous pemphigoid antigen 2) Ssc.20904.1.A1_at RAC-gamma serine/threonine- −1.34 3.01 −2.18 1.23 AKT3 enzastaurin protein kinase (RAC-PK-gamma) (Protein kinase Akt-3) (Protein kinase B, gamma) (PKB gamma) (STK-2) Ssc.26646.1.S1_at Glutamate receptor 1 −1.10 2.91 −5.42 −3.43 GRIA1 talampanel, Org 24448, LY451395, tezampanel Ssc.15312.1.S1_at Histone deacetylase 4 (HD4) −1.93 2.85 −2.41 1.20 HDAC4 tributyrin, PXD101, pyroxamide, vorinostat, FR 901228 Ssc.24889.1.S1_at Arachidonate 12-lipoxygenase, 1.97 2.83 −1.18 −2.78 ALOX12 sulfasalazine, balsalazide, 5- 12S-type aminosalicylic acid, masoprocol, verteporfin Ssc.12630.1.A1_at Sodium/potassium-transporting 2.97 2.81 −7.30 −2.03 ATP1A1 digoxin, omeprazole, ATPase alpha-1 chain ethacrynic acid, perphenazine Ssc.3040.1.S1_at Histone deacetylase 2 (HD2) −3.24 2.79 4.94 4.72 HDAC2 tributyrin, PXD101, pyroxamide, vorinostat, FR 901228 Ssc.12791.1.A1_at 3-hydroxy-3-methylglutaryl- 3.27 2.77 1.77 −2.56 HMGCR aspirin/pravastatin, coenzyme A reductase (HMG-CoA lovastatin/niacin, reductase) ezetimibe/simvastatin, amlodipine/atorvastatin, fluvastatin, cerivastatin, atorvastatin, pravastatin, simvastatin, lovastatin, rosuvastatin Ssc.20685.1.S1_at Apoptosis regulator Bcl-2 −2.22 2.77 2.58 3.25 BCL2 oblimersen, (−)-gossypol Ssc.15965.1.S1_at Inward rectifier potassium 4.68 2.72 −1.84 −4.62 KCNJ2 nicorandil, amiodarone channel 2 (Potassium channel, inwardly rectifying, subfamily J, member 2) (Inward rectifier K+ channel Kir2.1) (Cardiac inward rectifier potassium channel) (IRK1). Ssc.19673.1.S1_at T-cell surface glycoprotein 6.40 2.70 2.03 −11.77 CD3D visilizumab, MT103 CD3 delta chain precursor (T- cell receptor T3 delta chain) Ssc.16127.1.S1_at Adrenocorticotropic hormone −1.67 2.70 −2.51 −1.10 MC2R cosyntropin, ACTH receptor (ACTH receptor) (ACTH-R) Ssc.11406.1.A1_a_at Interleukin-1 receptor, type I 1.03 2.70 −2.44 1.42 IL1R1 anakinra precursor (IL-1R-1) (IL-1R- alpha) (P80) (Antigen CD121a) Ssc.19937.1.S1_at Inosine-5′-monophosphate 1.00 2.69 −1.47 3.65 IMPDH2 thioguanine, VX-944, dehydrogenase 2 (IMP interferon alfa-2a/ribavirin, dehydrogenase 2) mycophenolic acid, ribavirin Ssc.818.1.S1_at RAF proto-oncogene −1.40 2.56 1.58 1.98 RAF1 sorafenib serine/threonine-protein kinase Ssc.14129.1.A1_at 4-aminobutyrate aminotransferase, 6.91 2.56 −21.17 −3.35 ABAT valproic acid mitochondrial precursor (Gamma-amino-N-butyrate transaminase) (GABA transaminase) Ssc.13186.1.S1_at Cell division protein kinase 7 −1.08 2.38 4.34 1.24 CDK7 BMS-387032, flavopiridol Ssc.16167.1.S1_at Rho-associated protein kinase 2.40 2.32 2.83 3.00 ROCK1 fasudil, Y-27632 1 Ssc.6418.1.S1_at Farnesyl-diphosphate −1.25 2.31 1.33 1.08 FDFT1 TAK-475, zoledronic acid farnesyltransferase Ssc.15829.1.S1_at Retinoic acid receptor alpha −1.73 2.23 −1.33 −1.16 RARA etretinate, adapalene, arsenic trioxide, 13-cis-retinoic acid, tazarotene, acitretin, retinoic acid, 9-cis-retinoic acid Ssc.10142.1.A1_at Dihydropyrimidine 2.06 2.17 1.13 −2.68 DPYD eniluracil dehydrogenase [NADP+] (DPD) (DHPDHase) (Dihydrouracil dehydrogenase) (Dihydrothymine dehydrogenase). Ssc.23505.1.S1_at Amine oxidase [flavin- −1.86 2.17 1.08 1.20 MAOA ladostigil, 1- containing] A (Monoamine ethylphenoxathiin 10,10- oxidase) (MAO-A) dioxide, dextroamphetamine, procainamide, tranylcypromine, phenelzine, isocarboxazid, benzphetamine, N-(2- indanyl)glycinamide Ssc.20438.1.S1_at Prostaglandin F2-alpha −3.20 2.13 5.28 −38.97 PTGFR tafluprost, travoprost, receptor (Prostanoid FP isopropyl unoprostone, receptor) (PGF receptor) (PGF2 bimatoprost, latanoprost alpha receptor). Ssc.4756.1.A1_at Adenosine A3 receptor 2.15 2.10 1.88 −1.81 ADORA3 adenosine, dyphylline, aminophylline, clofarabine, theophylline, caffeine Ssc.11302.1.S1_at Collagen alpha 1(III) chain −1.80 2.02 2.06 1.26 COL3A1 collagenase Ssc.19400.2.A1_at Presenilin 2 (PS-2) (STM-2) −2.32 1.99 −5.30 −3.44 PSEN2 (R)-flurbiprofen (E5-1) (AD3LP) (AD5) Ssc.3059.1.S1_at Aldose reductase (AR) −1.74 1.98 −1.66 2.49 AKR1B1 sorbinil, Zopolrestat (Alond, (Aldehyde reductase). Pfizer), zenarestat (Fujisawa, Parke-Davis) Ssc.18051.1.S1_at cGMP-inhibited 3′,5′-cyclic −3.16 1.96 3.41 2.32 PDE3B dyphylline, nitroglycerin, phosphodiesterase B (Cyclic medorinone, aminophylline, GMP inhibited cilostazol, dipyridamole, phosphodiesterase B) (CGI-PDE amrinone, tolbutamide, B) (CGIPDE1) (CGIP1) theophylline, pentoxifylline Ssc.2548.1.S1_at DNA polymerase epsilon p17 2.27 1.93 −1.67 −1.21 POLE3 gemcitabine subunit (DNA polymerase epsilon subunit 3) (Chromatin accessibility complex 17) (HuCHRAC17) (CHRAC-17). Ssc.11383.1.A1_at Glutamate receptor 3 precursor 2.61 1.85 −1.87 −2.43 GRIA3 talampanel, Org 24448, (GluR-3) (GluR-C) (GluR-K3) LY451395, tezampanel (Glutamate receptor ionotropic, AMPA 3) Ssc.8549.1.A1_at Guanylate cyclase soluble, 1.11 1.84 −2.00 −2.59 GUCY1A3 nitroglycerin, isosorbide-5- alpha-3 chain (GCS-alpha-3) mononitrate, isosorbide (Soluble guanylate cyclase dinitrate, nitroprusside, large subunit) (GCS-alpha-1). isosorbide dinitrate/hydralazine Ssc.12781.1.A1_at Toll-like receptor 4 2.39 1.83 −1.52 −6.10 TLR4 TAK-242 Ssc.6301.1.S1_at Aromatic-L-amino-acid 1.76 1.80 −4.91 −1.88 DDC carbidopa/entacapone/levodopa, decarboxylase (AADC) (DOPA carbidopa/levodopa, S(−)- decarboxylase) carbidopa, L-dopa Ssc.6801.1.S1_at Proto-oncogene tyrosine- −1.06 1.69 2.36 −1.82 YES1 dasatinib protein kinase YES Ssc.5371.1.S1_a_at DNA polymerase epsilon subunit 10.16 1.68 −1.37 −3.14 POLE2 gemcitabine B (DNA polymerase II subunit B). Ssc.11572.1.A1_at Histone deacetylase 3 (HD3) −1.65 1.67 −1.55 2.36 HDAC3 tributyrin, PXD101, (RPD3-2) (SMAP45) pyroxamide, MGCD0103, vorinostat, FR 901228 Ssc.23234.1.S1_at collagen, type XXIV, alpha 1 −1.43 1.66 1.16 1.76 COL24A1 collagenase Ssc.9565.1.S1_at Interferon-gamma receptor 2.92 1.63 1.41 −1.23 IFNGR1 interferon gamma-1b alpha chain precursor (IFN- gamma-R1) (CD119 antigen) Ssc.5021.1.S1_at Glutamate decarboxylase, 65 −29.44 1.62 −10.79 −5.61 GAD2 valproic acid kDa isoform (GAD-65) (65 kDa glutamic acid decarboxylase) Ssc.14326.1.A1_at Mitogen-activated protein 12.63 1.56 −1.80 −7.24 MAPK13 SCIO-469 kinase 13 (Stress-activated protein kinase-4) (Mitogen- activated protein kinase p38 delta) (MAP kinase p38 delta) Ssc.10591.1.A1_at Metabotropic glutamate −7.83 1.54 −1.31 1.40 GRM5 fasoracetam receptor 5 precursor (mGluR5) Ssc.30373.1.A1_at cGMP-specific 3′,5′-cyclic 4.27 1.52 2.34 4.09 PDE5A dyphylline, nitroglycerin, DA- phosphodiesterase 8159, aminophylline, sildenafil, dipyridamole, aspirin/dipyridamole, vardenafil, tolbutamide, tadalafil, theophylline, pentoxifylline Ssc.6710.1.A1_at Ribonucleoside-diphosphate −1.90 1.44 2.01 −1.01 RRM1 gemcitabine, clofarabine, reductase M1 chain fludarabine phosphate (Ribonucleotide reductase large chain) Ssc.7139.1.S1_at Dihydrofolate reductase −1.13 1.41 −1.12 2.06 DHFR pyrimethamine, trimethoprim, iclaprim, methotrexate, sulfisoxazole, triamterene, folic acid, trimetrexate, LY231514, PT 523 Ssc.5538.1.S1_at Carbonic anhydrase II 8.09 1.39 −2.25 −1.35 CA2 methazolamide, (Carbonate dehydratase II) hydrochlorothiazide, (CA-II) (Carbonic anhydrase C) acetazolamide, trichloromethiazide, dorzolamide, chlorothiazide, dorzolamide/timolol, brinzolamide, chlorthalidone, benzthiazide, sulfacetamide, topiramate Ssc.5569.1.S1_at Thyroid hormone receptor alpha −10.22 1.26 1.26 6.49 THRA 3,5-diiodothyropropionic acid, (C-erbA-alpha) (c-erbA-1) amiodarone, thyroxine, L- (EAR-7) (EAR7) triiodothyronine Ssc.10360.1.S1_at B-Raf proto-oncogene −2.15 1.26 3.09 1.36 BRAF sorafenib serine/threonine-protein kinase Ssc.19672.1.S1_at RAC-alpha serine/threonine- 17.77 1.25 −19.82 −2.11 AKT1 enzastaurin protein kinase (RAC-PK-alpha) (Protein kinase B) (PKB) (C- AKT) Ssc.21011.1.S1_at Collagen alpha 2(I) chain −2.70 1.24 3.12 −1.01 COL1A2 collagenase Ssc.5045.1.S1_at 3-beta-hydroxysteroid- −1.55 1.24 2.19 2.08 EBP SR 31747 delta(8),delta(7)-isomerase (Cholestenol delta-isomerase) (Delta8-delta7 sterol isomerase) (D8-D7 sterol isomerase) (Emopamil-binding protein) Ssc.8726.1.A1_at Amidophosphoribosyltransferase 1.03 1.24 4.16 −1.11 PPAT 6-mercaptopurine, thioguanine, precursor (Glutamine azathioprine phosphoribosylpyrophosphate amidotransferase) (ATASE) (GPAT) Ssc.10219.1.A1_at Excitatory amino acid 1.36 1.24 −3.38 −1.03 SLC1A6 riluzole transporter 4 (Sodium- dependent glutamate/aspartate transporter) Ssc.15999.1.A1_at Vascular endothelial growth 1.24 1.24 18.52 −11.02 KDR AEE 788, sunitinib, AZD 2171, factor receptor 2 precursor pazopanib, XL647, CEP 7055, (VEGFR-2) (Kinase insert BMS-582664, KRN-951, vatalanib, domain receptor) (Protein- sorafenib, vandetanib, tyrosine kinase receptor Flk- pegaptanib 1) Ssc.9348.1.S1_at Peroxisome proliferator −1.05 1.22 −3.05 −1.52 PPARA NS-220, tesaglitazar, activated receptor alpha clofibrate, fenofibrate, (PPAR-alpha) docosahexaenoic acid, gemfibrozil Ssc.1498.1.S1_at Proteasome subunit beta type 5 −1.81 1.19 1.38 5.94 PSMB5 bortezomib precursor (Proteasome epsilon chain) (Macropain epsilon chain) (Multicatalytic endopeptidase complex epsilon chain) (Proteasome subunit X) (Proteasome chain 6) (Proteasome subunit MB1) Ssc.6934.1.A1_at Thymidylate synthase (EC −1.13 1.19 −1.11 −2.81 TYMS flucytosine, 5-fluorouracil, 2.1.1.45) (TS) (TSase) (OK/SW- plevitrexed, nolatrexed, cl.29) capecitabine, trifluridine, floxuridine, LY231514 Ssc.28329.1.S1_at DNA polymerase beta 1.14 1.19 1.07 5.25 POLB nelarabine, clofarabine, stavudine, trifluridine, vidarabine, zalcitabine, entecavir Ssc.16823.1.S1_at P2Y purinoceptor 12 (P2Y12) 1.38 1.19 1.41 1.11 P2RY12 prasugrel, AZD 6140 (P2Y12 platelet ADP receptor) (Ticagrelor), clopidogrel (P2Y(ADP)) (ADP-glucose receptor) (ADPG-R) (P2Y(AC)) (P2Y(cyc)) (P2T(AC)) (SP1999 Ssc.19691.1.S1_at Platelet-activating factor 1.59 1.16 3.01 1.47 PLA2G7 darapladib acetylhydrolase precursor (EC 3.1.1.47) (PAF acetylhydrolase) (PAF 2- acylhydrolase) (LDL-associated phospholipase A2) (LDL-PLA(2)) (2-acetyl-1- alkylglycerophosphocholine esterase) (1-alkyl-2- acetylglycerophosphocholine esterase) Ssc.15880.1.S1_at Cysteinyl leukotriene receptor 2.86 1.14 −2.12 −3.42 CYSLTR2 montelukast, zafirlukast 2 (CysLTR2) (PSEC0146) (HG57) (HPN321) (hGPCR21) Ssc.11147.1.S1_at Aldehyde dehydrogenase, 3.18 1.13 2.00 −1.68 ALDH2 disulfiram, chlorpropamide mitochondrial precursor (EC 1.2.1.3) (ALDH class 2) (ALDHI) (ALDH-E2) Ssc.1908.1.S1_at FKBP-rapamycin associated 1.99 1.13 −1.88 −1.46 FRAP1 AP23573, temsirolimus, protein (FRAP) (Rapamycin tacrolimus, everolimus target protein) Ssc.19700.1.S1_at Serine/threonine protein 1.11 1.13 1.34 1.09 PPP3CB ISAtx-247, tacrolimus, phosphatase 2B catalytic pimecrolimus, cyclosporin A subunit, beta Ssc.30147.1.A1_at Fibroblast growth factor 1.56 1.13 −1.05 −1.18 FGFR2 palifermin receptor 2 precursor (FGFR-2) (Keratinocyte growth factor receptor 2) Ssc.27232.1.S1_at Succinate semialdehyde 2.06 1.12 −2.84 −5.73 ALDH5A1 valproic acid dehydrogenase, mitochondrial precursor (NAD(+)-dependent succinic semialdehyde dehydrogenase) Ssc.10215.1.A1_at High-affinity cAMP-specific 1.83 1.12 −8.48 −15.51 PDE8A dyphylline, nitroglycerin, and IBMX-insensitive 3′,5′- aminophylline, anagrelide, cyclic phosphodiesterase 8A milrinone, dipyridamole, tolbutamide, theophylline, pentoxifylline Ssc.2767.2.S1_a_at Prostaglandin E2 receptor, EP3 2.30 1.12 −1.59 −6.78 PTGER3 prostaglandin E1 subtype (Prostanoid EP3 receptor) (PGE receptor, EP3 subtype) Ssc.15955.1.S1_at Antithrombin-III precursor −1.89 1.12 −2.06 −2.42 SERPINC1 enoxaparin, SR-123781A, (ATIII) (PRO0309) fondaparinux Ssc.25040.1.S1_at Serine/threonine-protein −3.75 1.11 1.06 −2.45 CHEK1 UCN-01 (7- kinase Chk1 hydroxystaurosporine) Ssc.14488.1.S1_at Glutamate carboxypeptidase II −1.04 1.10 1.02 1.69 FOLH1 capromab pendetide (Membrane glutamate carboxypeptidase) Ssc.1.1.S1_at 3-oxo-5-alpha-steroid 4- −1.77 1.05 −4.11 −1.09 SRD5A2 finasteride, dutasteride dehydrogenase 2 (Steroid 5- alpha-reductase 2) (SR type 2) (5 alpha-SR2) Ssc.7581.1.A1_at FL cytokine receptor precursor 1.69 1.04 −1.81 1.01 FLT3 CHIR-258, sorafenib, (Tyrosine-protein kinase lestaurtinib, CGP 41251 receptor FLT3) (Stem cell tyrosine kinase 1) (STK-1) (CD135 antigen)

TABLE 5 Day 60 prescription. Fold Fold Fold Fold Change Change Change Change D 7/ D 21/ D 60/ D 180/ Gene Probe ID Name Base Base Base Base Symbol DRUGS Ssc.21108.1.S1_at Complement C5 −17.35 3.21 618.80 9.28 C5 eculizumab Ssc.9272.1.S1_at Tumor-associated calcium 1.81 3.94 176.50 2.07 TACSTD1 tucotuzumab celmoleukin signal transducer 1 (EPCAM antigen) Ssc.23793.1.S1_at T-cell surface antigen CD2 −3.27 79.25 93.34 5.20 CD2 alefacept, siplizumab Ssc.17245.1.S1_at Interleukin-13 receptor alpha- −1.99 23.04 21.92 7.16 IL13RA1 cintredekin besudotox 1 chain Ssc.15999.1.A1_at Vascular endothelial growth 1.24 1.24 18.52 −11.02 KDR AEE 788, sunitinib, AZD 2171, factor receptor 2 pazopanib, XL647, CEP 7055, BMS- 582664, KRN-951, vatalanib, sorafenib, vandetanib, pegaptanib Ssc.27603.1.S1_at Endothelin B receptor 5.30 −3.27 15.99 1.23 EDNRB bosentan, sitaxsentan, precursor (ET-B) (Endothelin atrasentan receptor Non- selective type) Ssc.2714.1.S1_a_at Proto-oncogene tyrosine- −4.26 9.56 12.54 3.93 FYN dasatinib protein kinase FYN SscAffx.20.1.S1_at T-cell surface glycoprotein −2.19 14.07 10.96 3.62 CD3G visilizumab, MT103 CD3 gamma chain Ssc.7176.1.A1_at C-X-C chemokine receptor type 3.74 10.91 8.15 1.68 CXCR4 JM 3100 4 (CXC-R4) (CXCR-4) Ssc.26200.1.S1_at Thyroid hormone receptor beta- 3.49 −1.56 7.96 2.52 THRB 3,5-diiodothyropropionic acid, 1 amiodarone, thyroxine, L- triiodothyronine Ssc.7297.1.S1_at Amine oxidase [flavin- 1.16 6.42 7.02 −1.13 MAOB safinamide, ladostigil, containing] B(Monoamine rasagiline, selegiline, oxidase) (MAO-B). dextroamphetamine, procainamide, tranylcypromine, phenelzine, isocarboxazid, benzphetamine Ssc.9019.1.A1_at Atrial natriuretic peptide −1.09 −1.69 5.31 1.18 NPR3 nesiritide clearance receptor precursor (ANP-C) (ANPRC) Ssc.20438.1.S1_at Prostaglandin F2-alpha −3.20 2.13 5.28 −38.97 PTGFR tafluprost, travoprost, receptor isopropyl unoprostone, bimatoprost, latanoprost Ssc.3040.1.S1_at Histone deacetylase 2 (HD2) −3.24 2.79 4.94 4.72 HDAC2 tributyrin, PXD101, pyroxamide, vorinostat, FR 901228 Ssc.26325.1.S1_at Cystic fibrosis transmembrane 1.60 −5.71 4.77 −8.99 CFTR SP 303 conductance regulator (CFTR) Ssc.12845.1.S1_at Cell division protein kinase 6 −6.56 5.40 4.77 5.13 CDK6 PD-0332991, flavopiridol Ssc.13186.1.S1_at Cell division protein kinase 7 −1.08 2.38 4.34 1.24 CDK7 BMS-387032, flavopiridol Ssc.8726.1.A1_at Amidophosphoribosyltransferase 1.03 1.24 4.16 −1.11 PPAT 6-mercaptopurine, thioguanine, azathioprine Ssc.15374.1.S1_at COL14A1 protein 1.10 −17.71 3.79 2.24 COL14A1 collagenase Ssc.1147.1.A1_at Lipoprotein lipase 4.05 −5.49 3.78 −8.08 LPL nicotinic acid, lovastatin/niacin Ssc.15878.1.S1_at Serine/threonine protein 1.85 3.22 3.62 −1.49 PPP3CA ISAtx-247, tacrolimus, phosphatase 2B catalytic pimecrolimus, cyclosporin A subunit, alpha Ssc.26351.1.S1_at cAMP-specific 3′,5′-cyclic 4.67 4.99 3.61 −1.15 PDE4D dyphylline, nitroglycerin, phosphodiesterase 4D arofylline, tetomilast, L 869298, aminophylline, anagrelide, cilomilast, milrinone, rolipram, dipyridamole, L-826,141, roflumilast, tolbutamide, theophylline, pentoxifylline, caffeine Ssc.15801.1.A1_at Protein kinase C, beta 3.36 6.36 3.53 −4.98 PRKCB1 enzastaurin, ruboxistaurin Ssc.10055.1.A1_at Alpha platelet-derived growth −2.14 −1.46 3.52 −1.14 PDGFRA sunitinib, axitinib, imatinib, factor receptor becaplermin Ssc.24966.1.S1_at Purine nucleoside −3.34 3.12 3.46 −1.14 NP forodesine, 9-deaza-9-(3- phosphorylase thienylmethyl)guanine Ssc.18051.1.S1_at cGMP-inhibited 3′,5′-cyclic −3.16 1.96 3.41 2.32 PDE3B dyphylline, nitroglycerin, phosphodiesterase B medorinone, aminophylline, cilostazol, dipyridamole, amrinone, tolbutamide, theophylline, pentoxifylline Ssc.9523.1.A1_at Methylated-DNA--protein- 1.55 −1.17 3.35 1.47 MGMT O6-benzylguanine cysteine methyltransferase Ssc.16000.1.A1_at Vascular endothelial growth 1.08 −3.40 3.34 1.72 FLT1 sunitinib, axitinib, CEP 7055 factor receptor 1 Ssc.26328.1.S1_at C-C chemokine receptor type 5 −2.53 5.61 3.25 1.29 CCR5 maraviroc, vicriviroc, SCH (CCR5) (CD195 antigen). 351125 Ssc.17224.1.S1_at Toll-like receptor 8 1.17 6.49 3.13 −1.52 TLR8 resiquimod Ssc.21011.1.S1_at Collagen alpha 2(I) chain −2.70 1.24 3.12 −1.01 COL1A2 collagenase Ssc.10360.1.S1_at B-Raf proto-oncogene −2.15 1.26 3.09 1.36 BRAF sorafenib serine/threonine-protein kinase Ssc.19532.1.S1_at Guanylate cyclase soluble, −4.28 12.74 3.04 2.13 GUCY1B3 nitroglycerin, isosorbide-5- beta-1 chain mononitrate, isosorbide dinitrate, nitroprusside, isosorbide dinitrate/hydralazine Ssc.19691.1.S1_at Platelet-activating factor 1.59 1.16 3.01 1.47 PLA2G7 darapladib acetylhydrolase precursor Ssc.17155.1.A1_at heparanase; heparanase-1 4.81 5.38 2.98 −1.83 HPSE heparanase inhibitor PI-88 Ssc.15932.1.S1_at Integrin alpha-V precursor −6.15 5.79 2.94 3.14 ITGAV abciximab, CNTO 95, EMD121974 Ssc.16167.1.S1_at Rho-associated protein kinase 1 2.40 2.32 2.83 3.00 ROCK1 fasudil, Y-27632 Ssc.62.2.S1_a_at Interleukin-6 (IL-6) 1.89 −6.32 2.77 −1.04 IL6 tocilizumab Ssc.11246.1.A1_at Protein kinase C, alpha −5.96 −4.78 2.68 2.46 PRKCA L-threo-safingol Ssc.11381.1.S1_at Interferon-alpha/beta receptor 10.45 8.08 2.61 −1.30 IFNAR1 interferon beta-1a, interferon alpha alfa-2b, interferon alfacon-1, PEG-interferon alfa-2a, interferon alfa-2a/ribavirin, pegintron, interferon beta-1b, IFNA2A Ssc.20685.1.S1_at Apoptosis regulator Bcl-2 −2.22 2.77 2.58 3.25 BCL2 oblimersen, (−)-gossypol Ssc.12937.1.S1_at Presenilin 1 (PS-1) (S182 −14.09 6.21 2.48 3.79 PSEN1 (R)-flurbiprofen protein) Ssc.8500.1.A1_at Glutamate receptor 4 precursor −1.04 −1.13 2.39 −7.80 GRIA4 talampanel, Org 24448, LY451395, (GluR-4) (GluR4) (GluR-D) tezampanel (Glutamate receptor ionotropic, AMPA 4) Ssc.6801.1.S1_at Proto-oncogene tyrosine- −1.06 1.69 2.36 −1.82 YES1 dasatinib protein kinase YES Ssc.30373.1.A1_at cGMP-specific 3′,5′-cyclic 4.27 1.52 2.34 4.09 PDE5A dyphylline, nitroglycerin, DA- phosphodiesterase 8159, aminophylline, sildenafil, dipyridamole, aspirin/dipyridamole, vardenafil, tolbutamide, tadalafil, theophylline, pentoxifylline Ssc.15886.1.S1_at Apopain precursor (Caspase-3) −3.02 3.64 2.31 2.29 CASP3 IDN-6556 (CASP-3) Ssc.16114.1.S1_at Dihydropyridine-sensitive L- −1.96 −4.18 2.24 3.65 CACNA2D1 bepridil, amlodipine, pregabalin type, calcium channel alpha- 2/delta subunits Ssc.10256.1.A1_at cAMP-specific 3′,5′-cyclic −1.89 6.74 2.20 2.44 PDE4B dyphylline, nitroglycerin, phosphodiesterase 4B (EC arofylline, tetomilast, L 869298, 3.1.4.17) (DPDE4) (PDE32) aminophylline, anagrelide, cilomilast, milrinone, rolipram, dipyridamole, L-826,141, roflumilast, tolbutamide, theophylline, pentoxifylline, caffeine Ssc.5045.1.S1_at 3-beta-hydroxysteroid- −1.55 1.24 2.19 2.08 EBP SR 31747 delta(8),delta(7)-isomerase (Emopamil-binding protein) Ssc.204.1.S1_at Cytochrome P450 3A4 1.97 −3.35 2.16 −1.42 CYP3A4 ketoconazole Ssc.16186.1.S1_at T-cell surface glycoprotein 9.00 3.12 2.12 −5.66 CD3E visilizumab, MT103, muromonab- CD3 epsilon chain CD3 Ssc.1091.1.S1_at Collagen alpha 1(I) chain −3.27 −17.59 2.07 1.03 COL1A1 collagenase Ssc.11302.1.S1_at Collagen alpha 1(III) chain −1.80 2.02 2.06 1.26 COL3A1 collagenase Ssc.19673.1.S1_at T-cell surface glycoprotein 6.40 2.70 2.03 −11.77 CD3D visilizumab, MT103 CD3 delta chain Ssc.6710.1.A1_at Ribonucleoside-diphosphate −1.90 1.44 2.01 −1.01 RRM1 gemcitabine, clofarabine, reductase M1 chain fludarabine phosphate (Ribonucleotide reductase large chain) Ssc.11147.1.S1_at Aldehyde dehydrogenase, 3.18 1.13 2.00 −1.68 ALDH2 disulfiram, chlorpropamide mitochondrial precursor ((ALDHI) Ssc.1520.1.A1_at Proto-oncogene tyrosine- −1.05 −1.88 2.00 2.39 RET sunitinib protein kinase receptor ret Ssc.30888.1.S1_at Voltage-dependent L-type 2.92 −2.72 1.90 −7.82 CACNA1D MEM-1003, mibefradil, bepridil, calcium channel alpha-1D nisoldipine, isradipine, subunit nicardipine Ssc.15739.1.S1_at Cytokine receptor common gamma −1.12 9.42 1.90 −1.28 IL2RG aldesleukin, denileukin diftitox chain (IL-2R gamma chain) (CD132 antigen) Ssc.15822.1.S1_at Coagulation factor V 1.92 3.76 1.89 −1.75 F5 drotrecogin alfa (Activated protein C cofactor) Ssc.4756.1.A1_at Adenosine A3 receptor. 2.15 2.10 1.88 −1.81 ADORA3 adenosine, dyphylline, aminophylline, clofarabine, theophylline, caffeine Ssc.12791.1.A1_at 3-hydroxy-3-methylglutaryl- 3.27 2.77 1.77 −2.56 HMGCR aspirin/pravastatin, coenzyme A reductase (HMG-CoA lovastatin/niacin, reductase) ezetimibe/simvastatin, amlodipine/atorvastatin, fluvastatin, cerivastatin, atorvastatin, pravastatin, simvastatin, lovastatin, rosuvastatin Ssc.27293.1.A1_at Hypoxanthine-guanine 2.15 −1.16 1.63 −7.14 HPRT1 6-mercaptopurine, thioguanine, phosphoribosyltransferase azathioprine (HGPRT) Ssc.16189.1.S1_at Endothelin-1 receptor −1.11 −2.54 1.58 −2.91 EDNRA bosentan, avosentan, (Endothelin A receptor) (ET-A) clazosentan, ambrisentan, sitaxsentan, ZD4054, SB 234551, TBC 3214, BSF 302146, PD 180988, atrasentan Ssc.818.1.S1_at RAF proto-oncogene −1.40 2.56 1.58 1.98 RAF1 sorafenib serine/threonine-protein kinase Ssc.15748.2.S2_at T lymphocyte activation 1.95 −1.24 1.54 −3.12 CD80 abatacept antigen CD80 Ssc.19059.1.A1_at Type-1 angiotensin II receptor 5.57 −2.57 1.50 −11.08 AGTR1 amlodipine/olmesartan medoxomil, (AT1) (AT1AR) losartan/hydrochlorothiazide, valsartan/hydrochlorothiazide, candesartan cilexetil, olmesartan medoxomil, irbesartan, losartan potassium, telmisartan, eprosartan, candesartan cilexetil/hydrochlorothiazide, hydrochlorothiazide/irbesartan, eprosartan/hydrochlorothiazide, hydrochlorothiazide/telmisartan, hydrochlorothiazide/olmesartan medoxomil, valsartan Ssc.18459.1.S1_at Amiloride-sensitive sodium 1.97 −2.41 1.43 −1.93 SCNN1A triamterene/hydrochlorothiazide, channel alpha-subunit amiloride, amiloride/hydrochlorothiazide, triamterene Ssc.10287.1.A1_at Transforming growth factor 1.41 −4.54 1.43 1.67 TGFB2 AP-12009 beta 2 precursor (TGF-beta 2) Ssc.16823.1.S1_at P2Y purinoceptor 12 (P2Y12) 1.38 1.19 1.41 1.11 P2RY12 prasugrel, AZD 6140, clopidogrel (P2Y12 platelet ADP receptor) (P2Y(ADP)) Ssc.9565.1.S1_at Interferon-gamma receptor 2.92 1.63 1.41 −1.23 IFNGR1 interferon gamma-1b alpha chain Ssc.9595.1.S1_at Beta platelet-derived growth 3.48 −3.60 1.40 1.65 PDGFRB dasatinib, sunitinib, axitinib, factor receptor KRN-951, imatinib, sorafenib, becaplermin Ssc.8046.1.A1_at peptidylprolyl isomerase A 1.16 −1.08 1.39 1.26 PPIA N-methyl-4-Ile-cyclosporin isoform 1; cyclophilin A; Ssc.1498.1.S1_at Proteasome subunit beta type 5 −1.81 1.19 1.38 5.94 PSMB5 bortezomib Ssc.7111.1.A1_at Ribonucleoside-diphosphate −13.13 4.08 1.37 1.67 RRM2 gemcitabine, triapine, reductase M2 chain hydroxyurea, fludarabine (Ribonucleotide reductase phosphate small chain) Ssc.19700.1.S1_at Serine/threonine protein 1.11 1.13 1.34 1.09 PPP3CB ISAtx-247, tacrolimus, phosphatase 2B catalytic pimecrolimus, cyclosporin A subunit, beta Ssc.14258.1.S1_at Amyloid beta A4 protein 1.87 3.33 1.34 −1.02 APP AAB-001 precursor (APP) (ABPP) Ssc.6418.1.S1_at Farnesyl-diphosphate −1.25 2.31 1.33 1.08 FDFT1 TAK-475, zoledronic acid farnesyltransferase Ssc.16096.2.S1_a_at Mast/stem cell growth factor −1.28 −2.63 1.30 −4.71 KIT dasatinib, sunitinib, KRN-951, receptor imatinib, sorafenib Ssc.29149.1.A1_at Mineralocorticoid receptor −2.18 −2.78 1.28 −11.66 NR3C2 hydrochlorothiazide/spironolactone, (MR) fludrocortisone acetate, drospirenone, spironolactone, eplerenone Ssc.5569.1.S1_at Thyroid hormone receptor alpha −10.22 1.26 1.26 6.49 THRA 3,5-diiodothyropropionic acid, amiodarone, thyroxine, L- triiodothyronine Ssc.26215.1.S1_at DNA polymerase epsilon p12 −1.23 −2.71 1.19 −1.04 POLE4 gemcitabine subunit (DNA polymerase epsilon subunit 4) Ssc.23234.1.S1_at collagen, type XXIV, alpha 1 −1.43 1.66 1.16 1.76 COL24A1 collagenase Ssc.10142.1.A1_at Dihydropyrimidine 2.06 2.17 1.13 −2.68 DPYD eniluracil dehydrogenase [NADP+] Ssc.3607.1.S1_at Interferon-alpha/beta receptor 2.28 4.65 1.11 −1.56 IFNAR2 interferon beta-1a, interferon beta alfa-2b, interferon alfacon-1, PEG-interferon alfa-2a, interferon alfa-2a/ribavirin, pegintron, interferon beta-1b, IFNA2A Ssc.14475.3.S1_a_at Peroxisome proliferator 13.83 −9.38 1.09 −2.85 PPARG rosiglitazone, GI262570, activated receptor gamma pioglitazone, tesaglitazar, (PPAR-gamma) troglitazone Ssc.5000.1.A1_at Receptor protein-tyrosine −1.04 −4.15 1.08 2.25 ERBB2 trastuzumab, BMS-599626, ARRY- kinase erbB-2 334543, XL647, CP-724,714, HKI- 272, lapatinib, erlotinib Ssc.23505.1.S1_at Amine oxidase [flavin- −1.86 2.17 1.08 1.20 MAOA ladostigil, 1-ethylphenoxathiin containing] A (Monoamine 10,10-dioxide, dextroamphetamine, oxidase) (MAO-A) procainamide, tranylcypromine, phenelzine, isocarboxazid, benzphetamine, N-(2- indanyl)glycinamide Ssc.19379.1.A1_at Voltage-dependent L-type 1.83 −1.34 1.07 −3.27 CACNA1C clevidipine, MEM-1003, calcium channel alpha-1C amlodipine/olmesartan medoxomil, amlodipine/benazepril, diltiazem, verapamil, mibefradil, bepridil, enalapril/felodipine, amlodipine/atorvastatin, nisoldipine, isradipine, felodipine, nimodipine, nitrendipine, amlodipine, nicardipine, nifedipine, trandolapril/verapamil, diltiazem/enalapril Ssc.6713.1.S1_at Androgen receptor −1.47 −11.56 1.07 −2.36 AR estradiol valerate/testosterone (Dihydrotestosterone receptor) enanthate, estradiol cypionate/testosterone cypionate, bicalutamide, flutamide, nandrolone decanoate, testosterone cypionate, medroxyprogesterone acetate, oxandrolone, danazol, stanozolol, spironolactone, testosterone, oxymetholone, testosterone propionate, testosterone enanthate Ssc.28329.1.S1_at DNA polymerase beta 1.14 1.19 1.07 5.25 POLB nelarabine, clofarabine, stavudine, trifluridine, vidarabine, zalcitabine, entecavir Ssc.25040.1.S1_at Serine/threonine-protein −3.75 1.11 1.06 −2.45 CHEK1 UCN-01 (7-hydroxystaurosporine) kinase Chk1 Ssc.9781.1.S1_at Plasminogen activator −1.55 −1.17 1.04 1.30 SERPINE1 drotrecogin alfa inhibitor-1 (PAI-1) (Endothelial plasminogen activator inhibitor) (PAI) Ssc.16532.1.S1_at Cell division protein kinase 2 −1.83 −1.51 1.04 1.35 CDK2 BMS-387032, flavopiridol (p33 protein kinase). Ssc.22797.1.S1_at DNA topoisomerase II, beta 3.15 −1.87 1.02 −2.91 TOP2B novobiocin, etoposide, CPI- 0004Na, pixantrone, becatecarin, elsamitrucin, AQ4N, BN 80927, tafluposide, mitoxantrone, norfloxacin, dexrazoxane, tirapazamine, TAS-103, XK469, gatifloxacin, valrubicin, gemifloxacin, moxifloxacin, nemorubicin, nalidixic acid, epirubicin, doxorubicin, daunorubicin Ssc.14488.1.S1_at Glutamate carboxypeptidase II −1.04 1.10 1.02 1.69 FOLH1 capromab pendetide

TABLE 6 Day 180 prescription. Fold Fold Fold Fold Change Change Change Change D 7/ D 21/ D 60/ D 180/ Gene Probe ID Name Base Base Base Base Symbol DRUGS Ssc.11051.1.S1_at Cell division protein kinase 4 1.44 −7.67 −4.96 23.75 CDK4 PD-0332991, flavopiridol Ssc.28690.1.A1_at Histone deacetylase 6 (HD6) −1.92 −1.57 −3.58 20.60 HDAC6 tributyrin, PXD101, pyroxamide, vorinostat, FR 901228 Ssc.21108.1.S1_at Complement C5 −17.35 3.21 618.80 9.28 C5 eculizumab Ssc.5569.1.S1_at Thyroid hormone receptor alpha −10.22 1.26 1.26 6.49 THRA 3,5-diiodothyropropionic acid, amiodarone, thyroxine, L- triiodothyronine Ssc.1498.1.S1_at Proteasome subunit beta type 5 −1.81 1.19 1.38 5.94 PSMB5 bortezomib Ssc.13460.1.A1_at Histone deacetylase 9 (HD9) −6.40 5.13 −1.79 5.72 HDAC9 tributyrin, PXD101, pyroxamide, (HD7B) (HD7). vorinostat, FR 901228 Ssc.28329.1.S1_at DNA polymerase beta 1.14 1.19 1.07 5.25 POLB nelarabine, clofarabine, stavudine, trifluridine, vidarabine, zalcitabine, entecavir Ssc.23793.1.S1_at T-cell surface antigen CD2 −3.27 79.25 93.34 5.20 CD2 alefacept, siplizumab Ssc.12845.1.S1_at Cell division protein kinase 6 −6.56 5.40 4.77 5.13 CDK6 PD-0332991, flavopiridol Ssc.24528.1.S1_at Angiotensin-converting enzyme −1.61 5.01 2.33 4.76 ACE pentopril, perindoprilat, amlodipine/benazepril, lisinopril/hydrochlorothiazide, benazepril, enalapril, perindopril, captopril, enalapril/felodipine, hydrochlorothiazide/moexipril, benazepril/hydrochlorothiazide, hydrochlorothiazide/quinapril, fosinopril/hydrochlorothiazide, captopril/hydrochlorothiazide, enalapril/hydrochlorothiazide, ramipril, moexipril, quinapril, lisinopril, enalaprilat, trandolapril, trandolapril/verapamil, diltiazem/enalapril, fosinopril Ssc.3040.1.S1_at Histone deacetylase 2 (HD2) −3.24 2.79 4.94 4.72 HDAC2 tributyrin, PXD101, pyroxamide, vorinostat, FR 901228 Ssc.30373.1.A1_at cGMP-specific 3′,5′-cyclic 4.27 1.52 2.34 4.09 PDE5A dyphylline, nitroglycerin, DA- phosphodiesterase 8159, aminophylline, sildenafil, dipyridamole, aspirin/dipyridamole, vardenafil, tolbutamide, tadalafil, theophylline, pentoxifylline Ssc.2714.1.S1_a_at Proto-oncogene tyrosine- −4.26 9.56 12.54 3.93 FYN dasatinib protein kinase FYN Ssc.12937.1.S1_at Presenilin 1 (PS-1) (S182 −14.09 6.21 2.48 3.79 PSEN1 (R)-flurbiprofen protein). Ssc.19937.1.S1_at Inosine-5′-monophosphate 1.00 2.69 −1.47 3.65 IMPDH2 thioguanine, VX-944, interferon dehydrogenase 2 alfa-2a/ribavirin, mycophenolic acid, ribavirin Ssc.16114.1.S1_at Dihydropyridine-sensitive L- −1.96 −4.18 2.24 3.65 CACNA2D bepridil, amlodipine, type, calcium channel alpha- 1 pregabalin 2/delta SscAffx.20.1.S1_at T-cell surface glycoprotein −2.19 14.07 10.96 3.62 CD3G visilizumab, MT103 CD3 gamma chain Ssc.20685.1.S1_at Apoptosis regulator Bcl-2 −2.22 2.77 2.58 3.25 BCL2 oblimersen, (−)-gossypol Ssc.11443.1.A1_at Transcription factor p65 −1.43 −2.45 −3.96 3.24 RELA NF-kappaB decoy Ssc.26290.1.S1_at Integrin beta-5 −1.06 −1.51 −5.43 3.24 ITGB5 EMD121974 Ssc.15932.1.S1_at Integrin alpha-V −6.15 5.79 2.94 3.14 ITGAV abciximab, CNTO 95, EMD121974 Ssc.14471.1.S1_at B-lymphocyte antigen CD19 9.54 3.30 −10.32 3.04 CD19 combotox, HD37-dgRTA, MT103 Ssc.16167.1.S1_at Rho-associated protein kinase 2.40 2.32 2.83 3.00 ROCK1 fasudil, Y-27632 1 Ssc.26200.1.S1_at Thyroid hormone receptor beta- 3.49 −1.56 7.96 2.52 THRB 3,5-diiodothyropropionic acid, 1. amiodarone, thyroxine, L- triiodothyronine Ssc.3059.1.S1_at Aldose reductase (Aldehyde −1.74 1.98 −1.66 2.49 AKR1B1 sorbinil, Zopolrestat (Alond, reductase). Pfizer), zenarestat (Fujisawa, Parke-Davis) Ssc.11246.1.A1_at Protein kinase C, alpha −5.96 −4.78 2.68 2.46 PRKCA L-threo-safingol Ssc.10256.1.A1_at cAMP-specific 3′,5′-cyclic −1.89 6.74 2.20 2.44 PDE4B dyphylline, nitroglycerin, phosphodiesterase 4B arofylline, tetomilast, L 869298, aminophylline, anagrelide, cilomilast, milrinone, rolipram, dipyridamole, L-826, 141, roflumilast, tolbutamide, theophylline, pentoxifylline, caffeine Ssc.1598.1.S1_at Retinoic acid receptor RXR- −2.21 −1.13 −4.20 2.42 RXRB bexarotene, retinoic acid, 9- beta cis-retinoic acid Ssc.1520.1.A1_at Proto-oncogene tyrosine- −1.05 −1.88 2.00 2.39 RET sunitinib protein kinase receptor ret Ssc.11572.1.A1_at Histone deacetylase 3 (HD3) −1.65 1.67 −1.55 2.36 HDAC3 tributyrin, PXD101, pyroxamide, (RPD3-2) (SMAP45). MGCD0103, vorinostat, FR 901228 Ssc.18051.1.S1_at cGMP-inhibited 3′,5′-cyclic −3.16 1.96 3.41 2.32 PDE3B dyphylline, nitroglycerin, phosphodiesterase B medorinone, aminophylline, cilostazol, dipyridamole, amrinone, tolbutamide, theophylline, pentoxifylline Ssc.15886.1.S1_at Apopain precursor (Caspase-3) −3.02 3.64 2.31 2.29 CASP3 IDN-6556 (CASP-3) Ssc.5000.1.A1_at Receptor protein-tyrosine −1.04 −4.15 1.08 2.25 ERBB2 trastuzumab, BMS-599626, ARRY- kinase erbB-2 334543, XL647, CP-724,714, HKI- 272, lapatinib, erlotinib Ssc.15374.1.S1_at COL14A1 protein 1.10 −17.71 3.79 2.24 COL14A1 collagenase Ssc.19873.1.S1_at Collagen alpha 1(XVII) chain −2.37 3.02 −1.55 2.18 COL17A1 collagenase Ssc.19532.1.S1_at Guanylate cyclase soluble, −4.28 12.74 3.04 2.13 GUCY1B3 nitroglycerin, isosorbide-5- beta-1 chain mononitrate, isosorbide dinitrate, nitroprusside, isosorbide dinitrate/hydralazine Ssc.5045.1.S1_at 3-beta-hydroxysteroid- −1.55 1.24 2.19 2.08 EBP SR 31747 delta(8),delta(7)-isomerase (EC 5.3.3.5) (Cholestenol delta-isomerase) (Emopamil- binding protein). Ssc.9272.1.S1_at Tumor-associated calcium 1.81 3.94 176.50 2.07 TACSTD1 tucotuzumab celmoleukin signal transducer 1 (EPCAM antigen) Ssc.7139.1.S1_at Dihydrofolate reductase −1.13 1.41 −1.12 2.06 DHFR pyrimethamine, trimethoprim, iclaprim, methotrexate, sulfisoxazole, triamterene, folic acid, trimetrexate, LY231514, PT 523 Ssc.818.1.S1_at RAF proto-oncogene −1.40 2.56 1.58 1.98 RAFI sorafenib serine/threonine-protein kinase Ssc.25168.1.S1_a_at Collagen alpha 1(XVI) chain −7.23 −3.61 −4.45 1.87 COL16A1 collagenase Ssc.3737.1.S1_at Tubulin gamma-1 chain (Gamma-1 −1.24 −1.88 −1.29 1.82 TUBG1 epothilone B, ixabepilone, tubulin) ( colchicine/probenecid, XRP9881, E7389, AL 108, EC145, NPI-2358, milataxel, TPI 287, TTI-237, docetaxel, vinflunine, vinorelbine, vincristine, vinblastine, paclitaxel, podophyllotoxin, colchicine Ssc.23234.1.S1_at collagen, type XXIV, alpha 1 −1.43 1.66 1.16 1.76 COL24A1 collagenase Ssc.16000.1.A1_at Vascular endothelial growth 1.08 −3.40 3.34 1.72 FLT1 sunitinib, axitinib, CEP 7055 factor receptor 1 Ssc.14488.1.S1_at Glutamate carboxypeptidase II −1.04 1.10 1.02 1.69 FOLH1 capromab pendetide Ssc.7176.1.A1_at C-X-C chemokine receptor type 3.74 10.91 8.15 1.68 CXCR4 JM 3100 4 (CXC-R4) (CXCR-4) Ssc.10287.1.Al_at Transforming growth factor 1.41 −4.54 1.43 1.67 TGFB2 AP-12009 beta 2 Ssc.7111.1.A1_at Ribonucleos ide-diphosphate −13.13 4.08 1.37 1.67 RRM2 gemcitabine, triapine, reductase M2 chain hydroxyurea, fludarabine phosphate Ssc.9595.1.S1_at Beta platelet-derived growth 3.48 −3.60 1.40 1.65 PDGFRB dasatinib, sunitinib, axitinib, factor receptor KRN-951, imatinib, sorafenib, becaplermin Ssc.5826.1.A1_at Macrophage colony stimulating 1.93 −4.97 −13.18 1.61 CSF1R sunitinib factor I receptor Ssc.17518.1.S1_at Adenosine A1 receptor −3.16 3.44 −1.56 1.58 ADORA1 adenosine, dyphylline, aminophylline, clofarabine, theophylline, caffeine, tecadenos on Ssc.19691.1.S1_at Platelet-activating factor 1.59 1.16 3.01 1.47 PLA2G7 darapladib acetylhydrolase Ssc.9523.1.A1_at Methylated-DNA-protein- 1.55 −1.17 3.35 1.47 MGMT O6-benzylguanine cysteine methyltransferase Ssc.11406.1.A1_a_at Interleukin-1 receptor, type I 1.03 2.70 −2.44 1.42 IL1R1 anakinra Ssc.11085.1.S1_at Glucagon-like peptide 2 −1.08 −1.17 −1.26 1.40 GLP2R teduglutide receptor Ssc.10591.1.A1_at Metabotropic glutamate −7.83 1.54 −1.31 1.40 GRM5 fasoracetam receptor 5 Ssc.9034.1.A1_at Proteinase activated receptor −1.29 3.75 −1.40 1.37 F2R chrysalin, argatroban, 1 bivalirudin Ssc.10360.1.S1_at B-Raf proto-oncogene −2.15 1.26 3.09 1.36 BRAF sorafenib serine/threonine-protein kinase Ssc.16532.1.S1_at Cell division protein kinase 2 −1.83 −1.51 1.04 1.35 CDK2 BMS-387032, flavopiridol Ssc.9781.1.S1_at Plasminogen activator −1.55 −1.17 1.04 1.30 SERPINE drotrecogin alfa inhibitor-1 precursor (PAI-1) 1 (Endothelial plasminogen activator inhibitor) (PAI) Ssc.26328.1.S1_at C-C chemokine receptor type 5 −2.53 5.61 3.25 1.29 CCR5 maraviroc, vicriviroc, SCH (CCR5) (CD195 antigen) 351125 Ssc.8046.1.A1_at peptidylprolyl isomerase A 1.16 −1.08 1.39 1.26 PPIA N-methyl-4-Ile-cyclosporin isoform 1; cyclophilin A; Ssc.11302.1.S1_at Collagen alpha 1(III) chain −1.80 2.02 2.06 1.26 COL3A1 collagenase Ssc.13186.1.S1_at Cell division protein kinase 7 −1.08 2.38 4.34 1.24 CDK7 BMS-387032, flavopiridol Ssc.27603.1.S1_at Endothelin B receptor 5.30 −3.27 15.99 1.23 EDNRB bosentan, sitaxsentan, atrasentan Ssc.27093.1.A1_at cAMP-specific 3′,5′-cyclic −6.34 −2.27 −7.97 1.23 PDE4C dyphylline, nitroglycerin, phosphodiesterase 4C arofylline, tetomilast, L 869298, aminophylline, anagrelide, cilomilast, milrinone, rolipram, dipyridamole, L-826, 141, roflumilast, tolbutamide, theophylline, pentoxifylline, caffeine Ssc.20904.1.A1_at RAC-gamma serine/threonine- −1.34 3.01 −2.18 1.23 AKT3 enzastaurin protein kinase Ssc.23505.1.S1_at Amine oxidase [flavin- −1.86 2.17 1.08 1.20 MAOA ladostigil, 1-ethylphenoxathiin containing] A (Monoamine 10,10-dioxide, oxidase) (MAO-A) dextroamphetamine, procainamide, tranylcypromine, phenelzine, isocarboxazid, benzphetamine, N- (2-indanyl)glycinamide Ssc.15312.1.S1_at Histone deacetylase 4 (HD4) −1.93 2.85 −2.41 1.20 HDAC4 tributyrin, PXD101, pyroxamide, vorinostat, FR 901228 Ssc.9019.1.Al_at Atrial natriuretic peptide −1.09 −1.69 5.31 1.18 NPR3 nesiritide clearance receptor Ssc.16160.1.S1_at T lymphocyte activation −1.55 3.88 −1.37 1.18 CD86 abatacept antigen CD86 Ssc.1844.1.S1_at Atrial natriuretic peptide −1.94 −1.06 −1.63 1.13 NPR2 nesiritide receptor B Ssc.11171.1.S1_at Adenosine deaminase 1.32 −2.04 −3.23 1.12 ADA pentostatin, vidarabine Ssc.16823.1.S1_at P2Y purinoceptor 12 (P2Y12) 1.38 1.19 1.41 1.11 P2RY12 prasugrel, AZD 6140, (P2Y12 platelet ADP receptor) clopidogrel Ssc.19700.1.S1_at Serine/threonine protein 1.11 1.13 1.34 1.09 PPP3CB ISAtx-247, tacrolimus, phosphatase 2B catalytic pimecrolimus, cyclosporin A subunit, beta Ssc.26752.1.S1_at 5-hydroxytryptamine −3.57 1.22 1.60 1.08 HTR3B cisapride, granisetron, (serotonin) receptor 3B ondansetron, fenfluramine, palonosetron, mirtazapine, alosetron, D-tubocurarine, ergotamine, dolasetron Ssc.6418.1.S1_at Farnesyl-diphosphate −1.25 2.31 1.33 1.08 FDFT1 TAK-475, zoledronic acid farnesyltransferase Ssc.22477.1.S1_at Collagen alpha 1(IV) chain 1.58 −5.08 −1.78 1.04 COL4A1 collagenase Ssc.31192.1.S1_at Collagen alpha 1(XVIII) chain −1.89 −1.36 −19.06 1.03 COL18A1 collagenase Ssc.1091.1.S1_at Collagen alpha 1(I) chain −3.27 −17.59 2.07 1.03 COL1A1 collagenase Ssc.7581.1.A1_at FL cytokine receptor 1.69 1.04 −1.81 1.01 FLT3 CHIR-258, sorafenib, lestaurtinib, CGP 41251

TABLE 7 Upregulated gene targets at all timepoints (Days 7, 21, 60, and 180 relative to baseline) of PAH progression with available drugs Fold Fold Fold Fold Change Change Change Change D 7/ D 21/ D 60/ D 180/ Gene Probe ID Name Base Base Base Base Symbol Drugs Ssc.28329.1.S1_at DNA polymerase beta 1.14 1.19 1.07 5.25 POLB nelarabine, clofarabine, stavudine, trifluridine, vidarabine, zalcitabine, entecavir Ssc.9272.1.S1_at Tumor-associated 1.81 3.94 176.50 2.07 TACSTD1 tucotusumab celmoleukin calcium signal transducer 1 (EPCAM antigen) Ssc.7176.1.A1_at C-X-C chemokine 3.74 10.91 8.15 1.68 CXCR4 JM 3100 (1,1′-(1,4- receptor type 4 phenylenebis{methylene)}bis(1,4,8,11- (CXC-R4) (CXCR-4) (CD184 antigen) tetraazacyclotetradecane)octahydrochloride dihydrate) Ssc.19691.1.S1_at Platelet-activating 1.59 1.16 3.01 1.47 PLA2G7 darapladib factor acetylhydrolase Ssc.16823.1.S1_at P2Y purinoceptor 12 1.38 1.19 1.41 1.11 P2RY12 prasugrel, AZD 6140 (P2Y12) (Ticagrelor), clopidogrel Ssc.19700.1.S1_at Serine/threonine 1.11 1.13 1.34 1.09 PPP3CB ISAtx-247, tacrolimus, protein phosphatase pimecrolimus, cyclosporin A 2B catalytic subunit, beta isoform Ssc.14258.1.S1_at Amyloid beta A4 1.87 3.33 1.34 −1.02 APP Bapineuzumab (AAB-001) protein Ssc.8726.1.A1_at Amidophosphoribosyltransferase 1.03 1.24 4.16 −1.11 PPAT thioguanine, azathioprine, 6- mercaptopurine,

TABLE 8 Upregulated gene targets at Days 21 and 60 (relative to baseline) of PAH progression with available drugs Fold Fold Fold Fold Change Change Change Change D 7/ D 21/ D 60/ D 180/ Gene Probe ID Name Base Base Base Base Symbol Drugs Ssc.21108.1.S1_at Complement C5 −17.35 3.21 618.80 9.28 C5 eculizumab Ssc.9272.1.S1_at Tumor-associated 1.81 3.94 176.50 2.07 TACSTD1 tucctuzumab celmoleukin calcium signal transducer 1 Ssc.23793.1.S1_at T-cell surface −3.27 79.25 93.34 5.20 CD2 alefacept, siplizumab antigen CD2 Ssc.17245.1.S1_at Interleukin-13 −1.99 23.04 21.92 7.16 IL13RA1 cintredekin besudotox receptor alpha-1 chain Ssc.15999.1.A1_at Vascular endothelial 1.24 1.24 18.52 −11.02 KDR AEE 788, sunitinib, AZD 2171, growth factor pazopanib, XL647, CEP 7055, BMS-582664, KRN-951, vatalanib, sorafenib, vandetanib, receptor 2 pegaptanib Ssc.2714.1.S1_a_at Proto-oncogene −4.26 9.56 12.54 3.93 FYN dasatinib tyrosine-protein kinase FYN SscAffx.20.1.S1_at T-cell surface −2.19 14.07 10.96 3.62 CD3G visilizumab, MT103 glycoprotein CD3 gamma chain Ssc.7176.1.A1_at C-X-C chemokine 3.74 10.91 8.15 1.68 CXCR4 JM 3100 receptor type 4 (CXC-R4) (CXCR-4) ( Ssc.7297.1.S1_at Amine oxidase 1.16 6.42 7.02 −1.13 MAOB safinamide, ladostigil, rasagiline, [flavin-containing] selegiline, dextroamphetamine, B (EC 1.4.3.4) procainamide, tranylcypromine, (Monoamine oxidase) phenelzine, isocarboxazid, (MAO-B). benzphetamine Ssc.20438.1.S1_at Prostaglandin F2- −3.20 2.13 5.28 −38.97 PTGFR tafluprost, travoprost, isopropyl alpha receptor (PGF2 unoprostone, bimatoprost, latanoprost alpha receptor). Ssc.3040.1.S1_at Histone deacetylase −3.24 2.79 4.94 4.72 HDAC2 tributyrin, PXD101, pyroxamide, 2 (HD2). vorinostat, FR 901228 Ssc.12845.1.S1_at Cell division −6.56 5.40 4.77 5.13 CDK6 PD-0332991, flavopiridol protein kinase 6 (E Ssc.13186.1.S1_at Cell division −1.08 2.38 4.34 1.24 CDK7 BMS-387032, flavopiridol protein kinase 7 Ssc.8726.1.A1_at Amidophosphoribosyl- 1.03 1.24 4.16 −1.11 PPAT 6-mercaptopurine, thioguanine, transferase azathioprine Ssc.15878.1.S1_at Serine/threonine 1.85 3.22 3.62 −1.49 PPP3CA ISAtx-247, tacrolimus, pimecrolimus, protein phosphatase cyclosporin A 2B catalytic subunit, alpha isoform Ssc.26351.1.S1_at cAMP-specific 3′,5′- 4.67 4.99 3.61 −1.15 PDE4D dyphylline, nitroglycerin, arofylline, cyclic tetomilast, L 869298, aminophylline, phosphodiesterase 4D anagrelide, cilomilast, milrinone, (EC 3.1.4.17) rolipram, dipyridamole, L-826,141, (DPDE3) (PDE43). roflumilast, tolbutamide, theophylline, [Source: Uniprot/ pentoxifylline, caffeine SWISSPROT; Acc: Q08499] Ssc.15801.1.A1_at Protein kinase C, 3.36 6.36 3.53 −4.98 PRKCB1 enzastaurin, ruboxistaurin beta type (EC 2.7.1.37) (PKC-beta) (PKC-B). [Source: Uniprot/ SWISSPROT; Acc: P05771] Ssc.24966.1.S1_at Purine nucleoside −3.34 3.12 3.46 −1.14 NP forodesine, 9-deaza-9-(3- phosphorylase thiethylmethyl)guanine Ssc.18051.1.S1_at cGMP-inhibited −3.16 1.96 3.41 2.32 PDE3B syphylline, nitroglycerin, medorinone, 3′,5′-cyclic aminophylline, cilostazol, dipyridamole, phosphodiesterase B amrinone, tolbutamide, theophylline, pentoxifylline Ssc.26328.1.S1_at C-C chemokine −2.53 5.61 3.25 1.29 CCR5 maraviroc, vicriviroc, SCH 351125 receptor type 5 (C-C CKR-5) (CC-CKR-5) (CCR-5) (CCR5) (HIV- 1 fusion coreceptor) (CHEMR13) (CD195 antigen). [Source: Uniprot/ SWISSPROT; Acc: P51681] Ssc.17224.1.S1_at Toll-like receptor 8 1.17 6.49 3.13 −1.52 TLR8 resiquimod precursor. [Source: Uniprot/ SWISSPROT; Acc: Q9NR97] Ssc.21011.1.S1_at Collagen alpha 2(I) −2.70 1.24 3.12 −1.01 COL1A2 collagenase chain precursor. [Source: Uniprot/ SWISSPROT; Acc: P08123] Ssc.10360.1.S1_at B-Raf proto-oncogene −2.15 1.26 3.09 1.36 BRAF sorafenib serine/threonine- protein kinase (v- Raf murine sarcoma viral oncogene homolog B1). Ssc.19532.1.S1_at Guanylate cyclase −4.28 12.74 3.04 2.13 GUCY1B3 nitroglycerin, isosorbide-5-mononitrate, soluble, beta-1 isosorbide dinitrate, nitroprusside, isosorbide dinitrate/hydralazine Ssc.19691.1.S1_at Platelet-activating 1.59 1.16 3.01 1.47 PLA2G7 darapladib factor acetylhydrolase Ssc.17155.1.A1_at heparanase; 4.81 5.38 2.98 −1.83 HPSE heparanase inhibitor PI-88 heparanase-1 Ssc.15932.1.S1_at Integrin alpha-V −6.15 5.79 2.94 3.14 ITGAV abciximab, CNTO 95, EMD121974 (Cilengitide) Ssc.11381.1.S1_at Interferon- 10.45 8.08 2.61 −1.30 IFNAR1 interferon beta-1a, interferon alfa-2b, alpha/beta receptor interferon alfacon-1, PEG-interferon alfa- alpha chain 2a, interferon alfa-2a/ribavirin, precursor (IFN- pegintron, interferon beta-1b, IFNA2A alpha-REC). [Source: Uniprot/ SWISSPROT; Acc: P17181] Ssc.20685.1.S1_at Apoptosis regulator −2.22 2.77 2.58 3.25 BCL2 Oblimersen (Augmerosen), Bcl-2. [Source: Uniprot/ SWISSPROT; Acc: P10415] Ssc.12937.1.S1_at Presenilin 1 (PS-1) −14.09 6.21 2.48 3.79 PSEN1 (R)-flurbiprofen (Tarenflurbil) (S182 protein). Ssc.6801.1.S1_at Proto-oncogene −1.06 1.69 2.36 −1.82 YES1 dasatinib tyrosine-protein kinase YES Ssc.24528.1.S1_at Angiotensin- −1.61 5.01 2.33 4.76 ACE pentopril, perindoprilat, converting enzyme amlodipine/benazepril, lisinopril/hydrochlorothiazide, benazepril, enalapril, perindopril, captopril, enalapril/felodipine, hydrochlorothiazide/moexipril, benazepril/hydrochlorothiazide, hydrochlorothiazide/quinapril, fosinopril/hydrochlorothiazide, captopril/hydrochlorothiazide, enalapril/hydrochlorothiazide moexipril, quinapril, lisinopril, enalaprilat, trandolapril, trandolapril/verapamil, diltiazem/enalapril, fosinopril Ssc.15886.1.S1_at Apopain (Caspase-3) −3.02 3.64 2.31 2.29 CASP3 IDN-6556 (CASP-3 Ssc.10256.1.A1_at cAMP-specific 3′,5′- −1.89 6.74 2.20 2.44 PDE4B dyphylline, nitroglycerin, arofylline, cyclic tetomilast, L 869298, aminophylline, phosphodiesterase 4B anagrelide, cilomilast, milrinone, rolipram, dipyridamole, L-826, 141, roflumilast, tolbutamide, theophylline, pentoxifylline, caffeine Ssc.5045.1.S1_at 3-beta- −1.55 1.24 2.19 2.08 EBP SR 31747 hydroxysteroid- delta(8),delta(7)- isomerase Ssc.16145.1.A1_at 5-hydroxytryptamine 1.08 2.10 2.15 5.45 HTR2B risperidone, buspirone, blonanserin, 2B receptor (5-HT- asenapine, eletriptan, epinastine, 2B) (Serotonin fenfluramine, quetiapine, nefazodone, receptor 2B). mirtazapine, dihydroergotamine, apomorphine, ergotamine Ssc.16186.1.S1_at T-cell surface 9.00 3.12 2.12 −5.66 CD3E visilizumab, MT103, muromonab-CD3 glycoprotein CD3 epsilon chain Ssc.11302.1.S1_at Collagen alpha −1.80 2.02 2.06 1.26 COL3A1 collagenase 1(III) chain precursor. Ssc.19673.1.S1_at T-cell surface 6.40 2.70 2.03 −11.77 CD3D visilizumab, MT103 glycoprotein CD3 delta chain precursor (T-cell receptor T3 delta chain). Ssc.6710.1.A1_at Ribonucleoside- −1.90 1.44 2.01 −1.01 RRM1 gemcitabine, clofarabine, fludarabine diphosphate phosphate reductase M1 chain (Ribonucleotide reductase large chain Ssc.11147.1.S1_at Aldehyde 3.18 1.13 2.00 −1.68 ALDH2 disulfiram, chlorpropamide dehydrogenase, mitochondrial precursor (ALDH class 2) (ALDHI) (ALDH-E2). Ssc.15739.1.S1_at Cytokine receptor −1.12 9.42 1.90 −1.28 IL2RG aldesleukin, denileukin diftitox common gamma chain (Interleukin-2 receptor gamma chain) (IL-2R gamma chain) (CD132 antigen). Ssc.15822.1.S1_at Coagulation factor V 1.92 3.76 1.89 −1.75 F5 drotrecogin alfa precursor (Activated protein C cofactor). Ssc.4756.1.A1_at Adenosine A3 2.15 2.10 1.88 −1.81 ADORA3 adenosine, dyphylline, aminophylline, receptor. clofarabine, theophylline, caffeine Ssc.12791.1.A1_at 3-hydroxy-3- 3.27 2.77 1.77 −2.56 HMGCR aspirin/pravastatin, lovastatin/niacin, methylglutaryl- ezetimibe/simvastatin, coenzyme A reductase amlodipine/atorvastatin, fluvastatin, cerivastatin, atorvastatin, pravastatin, simvastatin, lovastatin, rosuvastatin Ssc.818.1.S1_at RAF proto-oncogene −1.40 2.56 1.58 1.98 RAF1 sorafenib serine/threonine- protein kinase Ssc.16823.1.S1_at P2Y purinoceptor 12 1.38 1.19 1.41 1.11 P2RY12 prasugrel, AZD 6140 (Ticagrelor), (P2Y12) (P2Y12 clopidogrel platelet ADP receptor) Ssc.9565.1.S1_at Interferon-gamma 2.92 1.63 1.41 −1.23 IFNGR1 interferon gamma-1b receptor alpha chain (CD119 antigen) Ssc.1498.1.S1_at Proteasome subunit −1.81 1.19 1.38 5.94 PSMB5 bortezomib beta type 5 Ssc.7111.1.A1_at Ribonucleoside- −13.13 4.08 1.37 1.67 RRM2 gemcitabine, triapine, hydroxyurea, diphosphate fludarabine phosphate reductase M2 chain Ssc.19700.1.S1_at Serine/threonine 1.11 1.13 1.34 1.09 PPP3CB ISAtx-247, tacrolimus, pimecrolimus, protein phosphatase cyclosporin A 2B catalytic subunit, beta Ssc.14258.1.S1_at Amyloid beta A4 1.87 3.33 1.34 −1.02 APP AAB-001 (Bapineuzumab) protein Ssc.6418.1.S1_at Farnesyl-diphosphate −1.25 2.31 1.33 1.08 FDFT1 TAK-475, zoledronic acid farnesyltransferase Ssc.5569.1.S1_at Thyroid hormone −10.22 1.26 1.26 6.49 THRA 3,5-diiodothyropropionic acid, receptor alpha (C- amiodarone, thyroxine, L-triiodothyronine erbA-alpha) (c-erbA- 1) Ssc.23234.1.S1_at collagen, type XXIV, −1.43 1.66 1.16 1.76 COL24A1 collagenase alpha 1 Ssc.10142.1.A1_at Dihydropyrimidine 2.06 2.17 1.13 −2.68 DPYD eniluracil dehydrogenase [NADP+] Ssc.3607.1.S1_at Interferon- 2.28 4.65 1.11 −1.56 IFNAR2 interferon beta-1a, interferon alfa-2b, alpha/beta receptor interferon alfacon-1, PEG-interferon alfa- beta chain 2a, interferon alfa-2a/ribavirin, pegintron, interferon beta-1b, IFNA2A Ssc.23505.1.S1_at Amine oxidase −1.86 2.17 1.08 1.20 MAOA ladostigil, 1-ethylphenoxathiin 10,10- [flavin-containing] A dioxide, dextroamphetamine, procainamide, tranylcypromine, phenelzine, isocarboxazid, benzphetamine, N-(2- indanyl)glycinamide Ssc.28329.1.S1_at DNA polymerase 1.14 1.19 1.07 5.25 POLB nelarabine, clofarabine, stavudine, trifluridine, vidarabine, zalcitabine, entecavir Ssc.25040.1.S1_at Serine/threonine- −3.75 1.11 1.06 −2.45 CHEK1 UCN-01 (7-hydroxystaurosporine) protein kinase Chk1 Ssc.26379.1.S1_at Glutamate [NMDA] −1.32 1.37 1.03 −2.59 GRIN2C dextromethorphan/guaifenesin, receptor subunit morphine/dextromethorphan, neramexane, epsilon 3 SPM 927, bicifadine, delucemine, CR 2249, besonprodil, UK-240455, ketamine, felbamate, memantine, orphenadrine, cycloserine, N-(2-indanyl)glycinamide, dextromethorphan, brompheniramine/ dextromethorphan/pseudoephedrine, chlorpheniramine/dextromethorphan/ phenylephrine, carbinoxamine/ dextromethorphan/pseudoephedrine, dextromethorphan/promethazine, 1- aminocyclopropane-1-carboxylic acid Ssc.14488.1.S1_at Glutamate −1.04 1.10 1.02 1.69 FOLH1 capromab pendetide carboxypeptidase II

TABLE 9 Upregulated gene targets at Days 21, 60 and 180 (relative to baseline) of PAH progression with available drugs Fold Fold Fold Fold Change Change Change Change D 7/ D 21/ D 60/ D 180/ Gene Probe ID Name Base Base Base Base Symbol Drugs Ssc.23793.1.S1_at T-cell surface −3.27 79.25 93.34 5.20 CD2 alefacept, siplizumab antigen CD2 SscAffx.20.1.S1_at T-cell surface −2.19 14.07 10.96 3.62 CD3G visilizumab, MT103 glycoprotein CD3 gamma chain Ssc.19532.1.S1_at Guanylate cyclase −4.28 12.74 3.04 2.13 GUCY1B3 nitroglycerin, isosorbide-5-mononitrate, soluble, beta-1 isosorbide dinitrate, nitroprusside, chain isosorbide dinitrate/hydralazine Ssc.7176.1.A1_at C-X-C chemokine 3.74 10.91 8.15 1.68 CXCR4 JM 3100 (1,1′-(1,4- receptor type 4 phenylenebis(methylene))bis(1,4,8,11- (CXC-R4) (CXCR-4) tetraazacyclotetradecane)octahydrochloride dihydrate) Ssc.2714.1.S1_a_at Proto-oncogene −4.26 9.56 12.54 3.93 FYN dasatinib tyrosine-protein kinase FYN Ssc.10256.1.A1_at cAMP-specific −1.89 6.74 2.20 2.44 PDE4B dyphylline, nitroglycerin, arofylline, 3′,5′-cyclic tetomilast, L 869298, aminophylline, phosphodiesterase anagrelide, cilomilast, milrinone, 4B rolipram, dipyridamole, L-826,141, roflumilast, tolbutamide, theophylline, pentoxifylline, caffeine Ssc.12937.1.S1_at Presenilin 1 (PS-1) −14.09 6.21 2.48 3.79 PSEN1 (R)-flurbiprofen (S182 protein). Ssc.15932.1.S1_at Integrin alpha-V −6.15 5.79 2.94 3.14 ITGAV abciximab, CNTO 95, EMD121974 (Cilengitide) Ssc.26328.1.S1_at C-C chemokine −2.53 5.61 3.25 1.29 CCR5 maraviroc, vicriviroc, SCH 351125 receptor type 5 (CCR5) Ssc.12845.1.S1_at Cell division −6.56 5.40 4.77 5.13 CDK6 PD-0332991, flavopiridol protein kinase 6 Ssc.24528.1.S1_at Angiotensin- −1.61 5.01 2.33 4.76 ACE pentopril, perindoprilat, converting enzyme amlodipine/benazepril, lisinopril/hydrochlorothiazide, benazepril, enalapril, perindopril, captopril, enalapril/felodipine, hydrochlorothiazide/moexipril, benazepril/hydrochlorothiazide, hydrochlorothiazide/quinapril, fosinopril/hydrochlorothiazide, captopril/hydrochlorothiazide, enalapril/hydrochlorothiazide, ramipril, moexipril, quinapril, lisinopril, enalaprilat, trandolapril, trandolapril/verapamil, diltiazem/enalapril, fosinopril Ssc.7130.1.S1_at Phenylalanine-4- 4.70 4.71 11.30 1.48 PAH (6R)-tetrahydrobiopterin hydroxylase Ssc.7111.1.A1_at Ribonucleoside- −13.13 4.08 1.37 1.67 RRM2 gemcitabine, triapine, hydroxyurea, diphosphate fludarabine phosphate reductase M2 chain (Ribonucleotide reductase small chain). Ssc.9272.1.S1_at Tumor-associated 1.81 3.94 176.50 2.07 TACSTD1 tucotuzumab celmoleukin calcium signal transducer 1 (EPCAM antigen) Ssc.15886.1.S1_at Apopain (Caspase- −3.02 3.64 2.31 2.29 CASP3 IDN-6556 3) (CASP-3) Ssc.21108.1.S1_at Complement C5 −17.35 3.21 618.80 9.28 C5 eculizumab Ssc.3040.1.S1_at Histone deacetylase −3.24 2.79 4.94 4.72 HDAC2 tributyrin, PXD101, pyroxamide, 2 (HD2). vorinostat, FR 901228 Ssc.20685.1.S1_at Apoptosis regulator −2.22 2.77 2.58 3.25 BCL2 oblimersen, (−)-gossypol Bcl-2 Ssc.818.1.S1_at RAF proto-oncogene −1.40 2.56 1.58 1.98 RAF1 sorafenib serine/threonine- protein kinase Ssc.13186.1.S1_at Cell division −1.08 2.38 4.34 1.24 CDK7 BMS-387032, flavopiridol protein kinase 7 Ssc.6418.1.S1_at Farnesyl- −1.25 2.31 1.33 1.08 FDFT1 TAK-475, zoledronic acid diphaosphate farnesyltransferase Ssc.23505.1.S1_at Amine oxidase −1.86 2.17 1.08 1.20 MAOA ladostigil, 1-ethylphenoxathiin 10,10- (flavin-containing) dioxide, dextroamphetamine, procainamide, A (Monoamine tranylcypromine, phenelzine, oxidase) (MAO-A). isocarboxazid, benzphetamine, N-(2- indanyl)glycinamide Ssc.11302.1.S1_at Collagen alpha −1.80 2.02 2.06 1.26 COL3A1 collagenase 1(III) chain precursor. Ssc.18051.1.S1_at cGMP-inhibited −3.16 1.96 3.41 2.32 PDE3B dyphylline, nitroglycerin, medorinone, 3′,5′-cyclic aminophylline, cilostazol, dipyridamole, phosphodiesterase B amrinone, tolbutamide, theophylline, pentoxifylline Ssc.23234.1.S1_at collagen, type −1.43 1.66 1.16 1.76 COL24A1 collagenase XXIV, alpha 1 Ssc.5569.1.S1_at Thyroid hormone −10.22 1.26 1.26 6.49 THRA 3,5-diiodothyropropionic acid, receptor alpha amiodarone, thyroxine, L-triiodothyronine Ssc.10360.1.S1_at B-Raf proto- −2.15 1.26 3.09 1.36 BRAF sorafenib oncogene serine/threonine- protein kinase Ssc.5045.1.S1_at 3-beta- −1.55 1.24 2.19 2.08 EBP SR 31747 hydroxysteroid- delta(8),delta(7)- isomerase Ssc.1498.1.S1_at Proteasome subunit −1.81 1.19 1.38 5.94 PSMB5 bortezomib beta type 5 Ssc.28329.1.S1_at DNA polymerase beta 1.14 1.19 1.07 5.25 POLB nelarabine, clofarabine, stavudine, trifluridine, vidarabine, zalcitabine, entecavir Ssc.16823.1.S1_at P2Y purinoceptor 12 1.38 1.19 1.41 1.11 P2RY12 prasugrel, AZD 6140, clopidogrel (P2Y12) (P2Y12 platelet ADP receptor) (P2Y(ADP)) Ssc.19691.1.S1_at Platelet-activating 1.59 1.16 3.01 1.47 PLA2G7 darapladib factor acetylhydrolase Ssc.19700.1.S1_at Serine/threonine 1.11 1.13 1.34 1.09 PPP3CB ISAtx-247, tacrolimus, pimecrolimus, protein phosphatase cyclosporin A 2B catalytic subunit, beta Ssc.14488.1.S1_at Glutamate −1.04 1.10 1.02 1.69 FOLH1 capromab pendetide carboxypeptidase II

TABLE 10 Upregulated gene targets at both Days 7 and 21 (relative to baseline) of PAH progression with available drugs Fold Fold Fold Fold Change Change Change Change D 7/ D 21/ D 60/ D 180/ Gene Probe ID Name Base Base Base Base Symbol Drugs Ssc.11381.1.S1_at Interferon-alpha/beta receptor 10.45 8.08 2.61 −1.30 IFNAR1 interferon beta-1a, alpha chain interferon alfa-2b, interferon alfacon-1, PEG- interferon alfa-2a, interferon alfa-2a/ribavirin, pegintron, interferon beta- 1b, IFNA2A Ssc.16186.1.S1_at T-cell surface glycoprotein 9.00 3.12 2.12 −5.66 CD3E visilizumab, MT103, CD3 epsilon chain muromonab-CD3 Ssc.19673.1.S1_at T-cell surface glycoprotein 6.40 2.70 2.03 −11.77 CD3D visilizumab, MT103 CD3 delta chain Ssc.17155.1.A1_at heparanase; heparanase-1 4.81 5.38 2.98 −1.83 HPSE heparanase inhibitor PI-88 Ssc.7130.1.S1_at Phenylalanine-4-hydroxylase 4.70 4.71 11.30 1.48 PAH (6R)-tetrahydrobiopterin Ssc.26351.1.S1_at cAMP-specific 3′,5′-cyclic 4.67 4.99 3.61 −1.15 PDE4D dyphylline, nitroglycerin, phosphodiesterase 4D arofylline, tetomilast, L869298, aminophylline, anagrelide, cilomilast, milrinone, rolipram, dipyridamole, L-826,141, roflumilast, tolbutamide, theophylline, pentoxifylline, caffeine Ssc.7176.1.A1_at C-X-C chemokine receptor 3.74 10.91 8.15 1.68 CXCR4 JM 3100 type 4 (CXC-R4) (CXCR-4) Ssc.15801.1.A1_at Protein kinase C, beta 3.36 6.36 3.53 −4.98 PRKCB1 enzastaurin, ruboxistaurin Ssc.12791.1.A1_at 3-hydroxy-3-methylglutaryl- 3.27 2.77 1.77 −2.56 HMGCR aspirin/pravastatin, coenzyme A reductase lovastatin/niacin, ezetimibe/simvastatin, amlodipine/atorvastatin, fluvastatin, cerivastatin, atorvastatin, pravastatin, simvastatin, lovastatin, rosuvastatin Ssc.11147.1.S1_at Aldehyde dehydrogenase, 3.18 1.13 2.00 −1.68 ALDH2 disulfiram, chlorpropamide mitochondrial Ssc.9565.1.S1_at Interferon-gamma receptor 2.92 1.63 1.41 −1.23 IFNGR1 interferon gamma-1b alpha chain Ssc.3607.1.S1_at Interferon-alpha/beta receptor 2.28 4.65 1.11 −1.56 IFNAR2 interferon beta-1a, beta interferon alfa-2b, interferon alfacon-1, PEG- interferon alfa-2a, interferon alfa-2a/ribavirin, pegintron, interferon beta- 1b, IFNA2A Ssc.4756.1.A1_at Adenosine A3 receptor. 2.15 2.10 1.88 −1.81 ADORA3 adenosine, dyphylline, aminophylline, clofarabine, theophylline, caffeine Ssc.10142.1.A1_at Dihydropyrimidine 2.06 2.17 1.13 −2.68 DPYD eniluracil dehydrogenase [NADP+] Ssc.15822.1.S1_at Coagulation factor V 1.92 3.76 1.89 −1.75 F5 drotrecogin alfa Ssc.14258.1.S1_at Amyloid beta A4 protein 1.87 3.33 1.34 −1.02 APP AAB-001 precursor (APP) (ABPP) Ssc.15878.1.S1_at Serine/threonine protein 1.85 3.22 3.62 −1.49 PPP3CA ISAtx-247, tacrolimus, phosphatase 2B catalytic pimecrolimus, cyclosporin A subunit, alpha Ssc.9272.1.S1_at Tumor-associated calcium 1.81 3.94 176.50 2.07 TACSTD1 tucotuzumab celmoleukin signal transducer 1 (EPCAM antigen) Ssc.19691.1.S1_at Platelet-activating factor 1.59 1.16 3.01 1.47 PLA2G7 darapladib acetylhydrolase Ssc.30147.1.A1_at Fibroblast growth factor 1.56 1.13 −1.05 −1.18 FGFR2 palifermin receptor 2 Ssc.16823.1.S1_at P2Y purinoceptor 12 (P2Y12) 1.38 1.19 1.41 1.11 P2RY12 prasugrel, AZD 6140, (P2Y12 platelet ADP receptor) clopidogrel Ssc.15999.1.A1_at Vascular endothelial growth 1.24 1.24 18.52 −11.02 KDR AEE 788, sunitinib, AZD factor receptor 2 2171, pazopanib, XL647, CEP 7055, BMS-582664, KRN-951, vatalanib, sorafenib, vandetanib, pegaptanib Ssc.17224.1.S1_at Toll-like receptor 8 1.17 6.49 3.13 −1.52 TLR6 resiquimod Ssc.7297.1.S1_at Amine oxidase 1.16 6.42 7.02 −1.13 MAOB safinamide, ladostigil, rasagiline, selegiline, dextroamphetamine, procainamide, tranylcypromine, phenelzine, isocarboxazid, benzphetamine Ssc.28329.1.S1_at DNA polymerase beta 1.14 1.19 1.07 5.25 POLB nelarabine, clofarabine, stavudine, trifluridine, vidarabine, zalcitabine, entecavir Ssc.19700.1.S1_at Serine/threonine protein 1.11 1.13 1.34 1.09 PPP3CB ISAtx-247, tacrolimus, phosphatase 2B catalytic pimecrolimus, cyclosporin A subunit, beta Ssc.8726.1.A1_at Amidophosphoribosyltransferase 1.03 1.24 4.16 −1.11 PPAT 6-mercaptopurine, precursor thioguanine, azathioprine

TABLE 11 Animal number, days after post-shunt PAH creation surgery, and pulmonary arterial pressure (PAP). Animal Day PAP PAP mean Pig 19 Timecourse P19 Day 0 28/1  26 P19 Day 10 22/17 19 P19 Day 24 76/29 47 P19 Day 59 89/50 58 P19 Day 94 70/18 54 Pig 20 Timecourse P20 Day 0 20/11 16 P20 Day 6 19/15 16 P20 Day 21 20/15 17 P20 Day 55 23/15 19 P20 Day 83 62/17 45 P20 Day 104 116/72  104 P20 Day 140 92/40 81 Normal (Normal Pressure & Flow) P19 Day 0 28/1  26 P20 Day 0 20/11 16 HFLP (High Flow Low Pressure) P19 Day 10 22/17 19 P20 Day 6 19/15 16 P20 Day 21 20/15 17 P20 Day 55 23/15 19 HFHP (High Flow High Pressure) P19 Day 24 76/29 47 P19 Day 59 89/50 58 P19 Day 94 70/18 54 P20 Day 83 62/17 45 P20 Day 104 116/72  104 P20 Day 140 92/40 81

TABLE 12 Significantly differently expressed downregulated microRNAs HFHP (High Flow High Pressure) vs. normal. Downregulated microRNA HFHP vs. Norm (p < .05) Illumina ID Normal HFHP HFLP miRNA Symbol ILMN_3167128 32.58 −2.36 2.75 solexa-603- 1846 ILMN_3167515 4183.74 42.62 142.81 hsa-miR-586 ILMN_3168604 31.83 −2.01 0.90 hsa-miR-1201 ILMN_3167691 127.02 1.76 1358.98 hsa-miR-33a ILMN_3167249 229.25 18.22 511.84 HS_56 ILMN_3167753 114.97 14.32 66.23 hsa-miR- 520d:9.1 ILMN_3168215 37.30 8.98 3110.35 hsa-miR-521 ILMN_3168168 32.58 1.72 28.59 hsa-miR-519a ILMN_3168054 3916.21 79.38 14.02 HS_134 ILMN_3168235 58.82 6.34 2.94 HS_169 ILMN_3168335 15.54 −2.85 26.65 HS_221 ILMN_3167393 90.38 5.18 5.54 hsa-miR-496 ILMN_3168678 837.14 14.23 777.94 hsa-miR-935 ILMN_3167175 8796.46 1274.47 88.95 hsa-miR-542-5p ILMN_3168905 92.30 5.07 33.55 solexa-5620- 151 ILMN_3168648 593.72 46.29 812.05 hsa-miR-99a ILMN_3167761 37.30 16.59 0.17 hsa-miR-212 ILMN_3168709 1281.24 218.10 80.10 hsa-let-7f-2 ILMN_3168446 8875.62 343.70 546.81 hsa-miR-494 ILMN_3168663 31.00 3.29 18.23 hsa-miR-1321 ILMN_3168597 99.25 14.28 43.96 hsa-miR-219-2- 3p ILMN_3166971 1310.30 311.18 924.85 hsa-miR-95 ILMN_3167491 3060.68 925.46 1647.50 hsa-miR- 128b:9.1 ILMN_3168654 740.78 96.90 957.01 hsa-miR-33a ILMN_3167052 370.00 45.81 234.11 hsa-miR-495 ILMN_3167337 177.30 43.83 27.93 hsa-miR-1229 ILMN_3168827 569.48 117.37 51.85 hsa-miR-1205 ILMN_3167328 6444.52 2162.76 2119.65 hsa-miR-524-3p ILMN_3167952 8724.37 2076.18 926.06 HS_150 ILMN_3168798 376.77 151.44 1348.57 hsa-miR-135a ILMN_3168558 211.48 68.62 28.31 hsa-miR-483-5p ILMN_3168039 9629.83 3219.90 7248.74 hsa-miR- 124a:9.1 ILMN_3168755 233.36 82.45 332.03 hsa-miR-29b-1 ILMN_3168540 493.90 161.33 304.45 hsa-miR-548c- 5p ILMN_3168265 11306.19 5572.32 6108.39 hsa-miR-551a ILMN_3168481 8687.78 4563.60 5504.04 hsa-miR-377 ILMN_3168882 12023.57 6677.06 8627.69 hsa-miR-1304

TABLE 13 Significantly differently expressed upregulated microRNAs HFHP (High Flow High Pressure) vs. normal. Upregulated microRNA HFHP vs. Norm (p < .05) Illumina ID Normal HFHP HFLP miRNA Symbol ILMN_3168350 −6.40 2772.39 12.69 hsa-miR-520g ILMN_3168706 −3.62 1700.55 8.11 hsa-miR-331-5p ILMN_3167244 −4.11 1534.57 −4.19 hsa-miR-410 ILMN_3168710 −3.08 1499.40 2147.63 hsa-let-7d ILMN_3168167 −4.14 1144.02 558.78 hsa-miR-187 ILMN_3168672 −4.20 941.07 162.41 hsa-miR-16-2 ILMN_3168870 −8.25 912.52 8.99 hsa-miR-130a ILMN_3168639 −4.96 728.32 −3.51 hsa-miR-548n ILMN_3168719 −1.17 380.69 −2.12 hsa-miR-127-5p ILMN_3168890 −4.11 343.04 530.05 solexa-2580- 353 ILMN_3168217 −5.60 304.34 −1.25 HS_206 ILMN_3167088 −5.06 303.57 −0.34 hsa-miR-663 ILMN_3168911 −1.32 235.62 61.24 solexa-7534- 111 ILMN_3168732 −0.63 216.74 12.96 hsa-let-7g ILMN_3167993 −6.45 192.76 237.96 HS_157 ILMN_3167193 −7.25 151.36 2130.07 hsa-miR-610 ILMN_3167879 −4.09 111.71 11.99 HS_251.1 ILMN_3168031 −4.54 52.02 15.76 hsa-miR-519e ILMN_3168818 −4.09 20.75 −0.83 hsa-miR-1237 ILMN_3168241 −2.10 18.57 649.52 hsa-miR-1185 ILMN_3167470 −4.18 12.39 7.90 HS_151.1 ILMN_3167512 −1.69 11.79 9.99 HS_135 ILMN_3168895 −2.86 7.81 0.75 solexa-3126- 285 ILMN_3167158 −0.63 3.36 739.08 hsa-miR-30a ILMN_3168722 1.26 529.41 430.69 hsa-miR-192 ILMN_3167039 17.25 1036.96 883.92 hsa-miR-568 ILMN_3168680 2.62 148.59 54.43 hsa-miR-1203 ILMN_3167223 381.67 5756.85 4105.59 hsa-miR-28-5p ILMN_3167361 21.39 259.94 255.04 HS_262.1 ILMN_3167684 11.78 80.14 21.38 HS_170 ILMN_3168760 11.78 80.09 26.17 hsa-miR-1273 ILMN_3167275 39.19 146.84 1900.87 hsa-miR-602 ILMN_3168240 1613.60 5725.95 4943.62 hsa-miR-374a ILMN_3168589 597.66 1739.42 928.77 hsa-miR-29a

TABLE 14 Significantly differently expressed downregulated microRNAs HFLP (High Flow Low Pressure) vs. normal. Downregulated microRNA HFLP vs. Norm (p < .05) Illumina ID Normal HFLP HFHP Gene Symbol ILMN_3167209 27.46 −3.19 1350.01 HS_104 ILMN_3168537 38.77 −0.76 57.24 hsa-miR-548a-5p ILMN_3167655 351.30 0.20 74.35 hsa-miR-556-5p ILMN_3168235 58.82 2.94 6.34 HS_169 ILMN_3167800 13.08 −2.83 1036.31 HS_140 ILMN_3167175 8796.46 88.95 1274.47 hsa-miR-542-5p ILMN_3168054 3916.21 14.02 79.38 HS_134 ILMN_3167761 37.30 0.17 16.59 hsa-miR-212 ILMN_3167509 17.25 −1.53 17.72 hsa-miR-363 ILMN_3167707 130.17 1.49 42.39 HS_59 ILMN_3167515 4183.74 142.81 42.62 hsa-miR-586 ILMN_3168446 8875.62 546.81 343.70 hsa-miR-494 ILMN_3168827 569.48 51.85 117.37 hsa-miR-1205 ILMN_3168709 1281.24 80.10 218.10 hsa-let-7f-2 ILMN_3168558 211.48 28.31 68.62 hsa-miR-483-5p ILMN_3167952 8724.37 926.06 2076.18 HS_150 ILMN_3167337 177.30 27.93 43.83 hsa-miR-1229 ILMN_3168305 31.00 5.36 34.52 HS_156 ILMN_3168490 67.94 18.69 106.29 hsa-miR-619 ILMN_3168573 776.09 190.47 805.44 hsa-miR-10b ILMN_3168586 887.48 304.35 617.25 hsa-miR-371-5p

TABLE 15 Significantly differently expressed upregulated microRNAs HFLP (High Flow Low Pressure) vs. normal. Upregulated microRNA HFLP vs. Norm (p < .05) Illumina ID Normal HFLP HFHP miRNA Symbol ILMN_3168010 −9.81 2363.55 689.66 HS_70 ILMN_3168710 −3.08 2147.63 1499.40 hsa-let-7d ILMN_3168167 −4.14 558.78 1144.02 hsa-miR-187 ILMN_3168890 −4.11 530.05 343.04 solexa-2580-353 ILMN_3167993 −6.45 237.96 192.76 HS_157 ILMN_3168911 −1.32 61.24 235.62 solexa-7534-111 ILMN_3168870 −8.25 8.99 912.52 hsa-miR-130a ILMN_3167512 −1.69 9.99 11.79 HS_135 ILMN_3168722 1.26 430.69 529.41 hsa-miR-192 ILMN_3167720 2.62 145.01 147.62 hsa-miR-154 ILMN_3167062 78.98 2184.01 1423.21 hsa-miR-151:9.1 ILMN_3168680 2.62 54.43 148.59 hsa-miR-1203 ILMN_3167778 24.39 206.06 81.33 hsa-miR-525-3p ILMN_3167749 37.30 226.26 272.25 HS_199

TABLE 16 Significantly differently expressed upregulated microRNAs HFHP vs. HFLP. Upregulated microRNA HFHP vs. HFLP (p < .05) Illumina ID Normal HFHP HFLP miRNA Symbol ILMN_3167244 −4.11 1534.57 −4.19 has-miR-410 ILMN_3168639 −4.96 728.32 −3.51 has-miR-548n ILMN_3168537 38.77 57.24 −0.76 has-miR-548a-5p ILMN_3168613 4.53 18.13 −0.99 has-miR-185 ILMN_3168047 34.59 10.25 −4.94 HS_3 ILMN_3167440 71.49 −0.51 −4.89 HS_67 ILMN_3168585 45.00 97.09 2.43 has-miR-1250 ILMN_3168543 140.56 2778.92 47.17 has-miR-5481 ILMN_3168221 52.52 216.12 13.76 has-miR-548c-3p ILMN_3167831 31.83 186.98 12.94 has-miR-520d-5p ILMN_3167105 292.19 174.71 25.34 has-miR-208b ILMN_3167313 475.92 793.85 135.08 HS_200 ILMN_3168634 892.54 1830.74 479.17 has-miR-218-1 ILMN_3168247 390.00 300.41 111.54 has-miR-643

TABLE 17 Significantly differently expressed downregulated microRNAs HFHP vs. HFLP. Downregulated microRNA HFHP vs. HFLP (p < .05) Illumina ID Normal HFHP HFLP miRNA Symbol ILMN_3167778 24.39 81.33 206.06 hsa-miR-525-3p ILMN_3167052 370.00 45.81 234.11 hsa-miR-495 ILMN_3168052 176.33 116.43 480.71 HS_250 ILMN_3168863 9.59 1.11 46.30 hsa-miR-933 ILMN_3168848 13.53 8.90 475.98 hsa-miR-1287 ILMN_3168750 784.33 2850.15 8118.48 hsa-miR-1308 ILMN_3168348 10.81 9.66 553.87 hsa-miR-133b ILMN_3166995 1.97 1.33 254.82 HS_215 ILMN_3167545 42.85 10.92 23.89 HS_115 ILMN_3168819 756.53 1345.27 5334.48 hsa-miR-151-5p ILMN_3167249 229.25 18.22 511.84 HS_56 ILMN_3168010 −9.81 689.66 2363.55 HS_70 ILMN_3168215 37.30 8.98 3110.35 hsa-miR-521 

We claim:
 1. A method of diagnosing a vascular-related disease in an individual comprising the steps of: a) identifying at least one gene that is upregulated or downregulated in the vascular-related disease comprising the steps of: 1) obtaining a biopsy sample from the individual's artery during progression of the vascular-related disease; 2) obtaining an artery sample from a non-diseased control; 3) extracting RNA from the samples in steps 1) and 2); 4) obtaining gene products from the RNA extracted in steps 3); and 5) comparing gene expression levels from the biopsy sample with the non-diseased control; and b) associating the genes upregulated in the biopsy sample with an inhibitor of the gene products for administration to the individual and genes downregulated in the biopsy sample with a promoter of the gene products for administration to the individual.
 2. The method of claim 1, wherein the vascular-related disease is pulmonary arterial hypertension.
 3. The method of claim 1, wherein the biopsy sample is extracted using an endoarterial catheter.
 4. A method of identifying microRNA dysregulated in an individual having a vascular-related disease comprising the steps of: a) obtaining a biopsy sample from the individual's artery during progression of the vascular-related disease; b) obtaining an artery sample from a non-diseased control; c) extracting RNA from the samples in steps a) and b); d) converting the RNA to cDNA; e) comparing levels of microRNA expression from the biopsy sample with the non-diseased control; and f) identifying the microRNA dysregulated in the vascular-related disease relative to baseline.
 5. The method of claim 4, wherein the vascular-related disease is pulmonary arterial hypertension.
 6. The method of claim 4, wherein the microRNA is measured according to stages of progression of the vascular-related disease.
 7. A use of targeting microRNAs in the preparation of a medicament for the treatment of a vascular-related disease comprising the following steps: a) assessing a stage of the vascular-related disease in the individual; b) identifying whether microRNAs are upregulated or downregulated; c) selecting the microRNAs to target based on the stage of the vascular-related disease and whether the microRNAs are upregulated or downregulated; and d) administering an agent known to inhibit an upregulated microRNA or an agent known to promote downregulated microRNA to the individual, wherein the stage of the vascular-related disease is based on flow rates and blood pressure within an artery of the individual.
 8. The use of claim 7, wherein the vascular-related disease is pulmonary arterial hypertension.
 9. The use of claim 7, wherein the microRNAs to target are selected from the group consisting of Tables 12-17.
 10. The use of claim 7, wherein the stage of the vascular-related disease of one of high flow and high pressure within the artery of the individual.
 11. The use of claim 10, wherein the upregulated microRNAs to inhibit under the stage of high flow and high pressure comprise at least one member selected from the group consisting of hsa-miR-520g, hsa-miR-331-5p, hsa-miR-410, has-let-7d, hsa-miR-187, hsa-miR-16-2, hsa-miR-130a, hsa-miR-548n, hsa-miR-127-5p, solexa-2580-353, HS_206, hsa-miR-663, solexa-7534-111, hsa-let-7g, HS_157, hsa-miR-610, HS_251.1, hsa-miR-519e, hsa-miR-1237, hsa-miR-1185, HS_151.1, HS_135, solexa-3126-285, hsa-miR-30a, hsa-miR-192, hsa-miR-568, hsa-miR-1203, hsa-miR-28-5p, HS_262.1, HS_170, hsa-miR-1273, hsa-miR-602, hsa-miR-374a and hsa-miR-29a.
 12. The use of claim 7, wherein the stage of the vascular-related disease is one of high flow and low pressure within the artery of the individual.
 13. The use of claim 12, wherein the upregulated microRNAs to inhibit under the stage of high flow and low pressure comprise at least one member selected from the group consisting of HS_70, hsa-let-7d, hsa-miR-187, solexa-2580-353, HS_157, solexa-7534-111, hsa-miR-130a, HS_135, hsa-miR-192, hsa-miR-154, hsa-miR-151:9.1, hsa-miR-1203, hsa-miR-525-3p, and HS_199.
 14. The use of claim 10, wherein the downregulated microRNAs to promote under the stage of high flow and high pressure comprise at least one member selected from the group consisting of solexa-603-1846, hsa-miR-586, hsa-miR-1201, hsa-miR-33a, HS_56, hsa-miR-520d:9.1, hsa-miR-521, hsa-miR-519a, HS_134, HS_169, HS_221, hsa-miR-496, hsa-miR-935, hsa-miR-542-5p, solexa-5620-151, hsa-miR-99a, hsa-miR-212, hsa-let-7f-2, hsa-miR-494, hsa-miR-1321, hsa-miR-219-2-3p, hsa-miR-95, hsa-miR-128b:9.1, hsa-miR-33a, hsa-miR-495, hsa-miR-1229, hsa-miR-1205, hsa-miR-524-3p, HS_150, hsa-miR-135a, hsa-miR-483-5p, hsa-miR-124a:9.1, hsa-miR-29b-1, hsa-miR548c-5p, hsa-miR-551a, hsa-miR-377 and hsa-mir-1304.
 15. The use of claim 12, wherein the downregulated microRNAs to promote under the stage of high flow and low pressure comprise at least one member selected from the group consisting of HS_104, hsa-miR-548a-5p, hsa-miR-556-5p, HS_169, HS_140, hsa-miR-542-5p, HS_134, hsa-miR-212, hsa-miR-363, HS_59, hsa-miR-586, hsa-miR-494, hsa-miR-1205, hsa-let-7f-2, hsa-miR-483-5p, HS_150, hsa-miR-1229, HS_156, hsa-miR-619, hsa-miR-10b and hsa-miR-371-5p.
 16. A method of diagnosing an individual having a vascular-related disease according to claim 1, further wherein the individual is categorized based on progression of the vascular-related disease.
 17. The method of claim 16, wherein the progression of the vascular-related disease is selected from the group consisting of early stage, mid stage and late stage.
 18. The method of claim 1, wherein the diagnosing of the individual may be modified over the course of disease progression. 